Transdisciplinary role of physical and mathematical disciplines in modern natural science and engineering education by V. A. Testov, E. A. Perminov

“…As a result of the transdisciplinary trend in science, such scientific fields as cybernetics, general systems theory, catastrophe theory, synergetics, artificial intelligence, big data, etc. have emerged. …”
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Advanced Extensions and Applications of Transitivity and Mixing in Set-Valued Dynamics With Numerical Simulations and Visual Insights by Illych Alvarez

“…These simulations provide a visual and computational tool to better understand the dynamics of set-valued maps, making abstract theories more accessible and engaging. …”
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Dempster Shafer-Empowered Machine Learning-Based Scheme for Reducing Fire Risks in IoT-Enabled Industrial Environments by Jayameena Desikan, Sushil Kumar Singh, A. Jayanthiladevi, Saurabh Singh, Byungun Yoon

“…Traditional fire detection systems that rely on single IoT sensors, like heat or smoke detectors, are prone to inaccuracies and delayed responses, particularly in noisy or complex industrial environments. This research proposes an advanced fire prediction approach aiming to enhance decision-making accuracy with uncertain or incomplete fire sensor data in an edge computing IoT complex industrial environment that integrates multiple supervised machine learning algorithms for each sensor types and Dempster-Shafer theory (DST) with multi-sensor fusion. …”
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Dual Szegö pairs of sequences of rational matrix-valued functions by Andreas Lasarow

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Dynamic analysis and Chaos control in a discrete predator-prey model with Holling type IV and nonlinear harvesting by Karima Mokni, Mohamed Ch-Chaoui

“…Finally, we use numerical simulations and computer analysis to check our theories and show more complex behaviors.…”
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On Training Spiking Neural Networks by Means of a Novel Quantum Inspired Machine Learning Method by Jean Michel Sellier, Alexandre Martini

“…., temporal patterns), training them remains an open and complex problem. In practice, while in theory these networks are computationally as powerful as mainstream artificial neural networks, they have not reached the same accuracy levels yet. …”
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Adaptive mechanisms of social and asocial learning in immersive collective foraging by Charley M. Wu, Dominik Deffner, Benjamin Kahl, Björn Meder, Mark K. Ho, Ralf H.J.M. Kurvers

“…These findings not only integrate theories across asocial and social domains, but also provide key insights into the adaptability of human decision-making in complex and dynamic social landscapes.…”
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COMPUTAÇÃO QUÂNTICA EM QUÍMICA by Caio M. Porto, Matheus S. Fonseca, Guilherme de S. T. Morais, Celso J. Villas-Boas, Rene A. Nome, Nelson H. Morgon

“…QUANTUM COMPUTING IN CHEMISTRY. Quantum computing offers transformative potential for quantum chemistry, enabling the exploration of complex molecular simulations with unprecedented accuracy. …”
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On the Inverse Eigenvalue Problem for Irreducible Doubly Stochastic Matrices of Small Orders by Quanbing Zhang, Changqing Xu, Shangjun Yang

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A Topology Construct and Control Model with Small-World and Scale-Free Concepts for Heterogeneous Sensor Networks by Lifang Liu, Xiaogang Qi, Jilong Xue, Mande Xie

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DIKWP-TRIZ: A Revolution on Traditional TRIZ Towards Invention for Artificial Consciousness by Kunguang Wu, Yucong Duan

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Expectation of individual packet transmission times in reliable broadcast by Kai-yun WANG, You-ping LI, Si-qi KONG, Qiang1 ZHAO, Wei-dong MA

“…The mathematical expectation of individual packet transmission times was a fundamental parameter in the theory of reli-able broadcast. Up to now, there were two categories of solutions for this parameter in relevant literatures: exact series solutions and approximate solutions used for analyzing complexities. …”
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Conductivities and excitations of a holographic flavour brane Weyl semimetal by Haruki Furukawa, Sacha Ployet, Ronnie Rodgers

“…Abstract We compute the electrical conductivities at non-zero frequency in a top-down holographic model of a Weyl semimetal, consisting of N $$ \mathcal{N} $$ = 4 supersymmetric SU(N c ) Yang-Mills theory coupled to N $$ \mathcal{N} $$ = 2 hypermultiplets with mass m, subject to an applied axial vector field b. …”
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Morphology in children’s books, and what it means for learning by Maria Korochkina, Kathleen Rastle

“…Abstract Breaking down complex words into smaller meaningful units (e.g., unhappy = un- + happy), known as morphemes, is vital for skilled reading as it allows readers to rapidly compute word meanings. …”
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Exploring the energy landscape of RBMs: reciprocal space insights into bosons, hierarchical learning and symmetry breaking by J Quetzalcóatl Toledo-Marin, Anindita Maiti, Geoffrey C Fox, Roger G Melko

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Stability analysis of N-D discrete state–space systems by Apostolos Kanellakis, Ayman Tawfik, Panajotis Agathoklis

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A Novel Generalized Interval-Valued Neutrosophic Rough Soft Set Framework for Enhanced Decision-Making: Application in Water Quality Assessment by Anjan Mukherjee, Ajoy Kanti Das, Nandini Gupta, Suman Patra, Tahir Mahmood, Suman Das, Rakhal Das

“…<p>This study introduces a novel framework, Generalized Interval-Valued Neutrosophic Rough Soft Sets (GIVNRS sets), designed to improve handling uncertainty, imprecision, and vagueness in complex decision-making scenarios. By integrating soft, rough, and generalized interval-valued neutrosophic set theories, the framework offers a robust methodology for addressing indeterminacy and incomplete data. …”
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Study on Mechanism Experiments and Evaluation Methods for Water Eutrophication by Jiabin Yu, Zhaoyang Wang, Xiaoyi Wang, Jiping Xu, Jie Jia

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Efficient Resources Provisioning Based on Load Forecasting in Cloud by Rongdong Hu, Jingfei Jiang, Guangming Liu, Lixin Wang

“…We propose a multi-step-ahead load forecasting method, KSwSVR, based on statistical learning theory which is suitable for the complex and dynamic characteristics of the cloud computing environment. …”
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Quantum black holes: Perihelion advance, quasi normal modes and classical/topological thermodynamics by Grigoris Panotopoulos, Francisco Tello-Ortiz

“…We find that all modes computed here are complex numbers characterized by a positive real part and a negative imaginary part, while both parts increase with the mass of the test scalar field. …”
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