The Influence of Neural Networks on Hydropower Plant Management in Agriculture: Addressing Challenges and Exploring Untapped Opportunities

Hydropower plants are crucial for stable renewable energy and serve as vital water sources for sustainable agriculture. However, it is essential to assess the current water management practices associated with hydropower plant management software. A key concern is the potential conflict between electricity generation and agricultural water needs. Prioritising water for electricity generation can reduce irrigation availability in agriculture during crucial periods like droughts, impacting crop yields and regional food security. Coordination between electricity and agricultural water allocation is necessary to ensure optimal and environmentally sound practices. Neural networks have become valuable tools for hydropower plant management, but their black-box nature raises concerns about transparency in decision making. Additionally, current approaches often do not take advantage of their potential to create a system that effectively balances water allocation. This work is a call for attention and highlights the potential risks of deploying neural network-based hydropower plant management software without proper scrutiny and control. To address these concerns, we propose the adoption of the Agriculture Conscious Hydropower Plant Management framework, aiming to maximise electricity production while prioritising stable irrigation for agriculture. We also advocate reevaluating government-imposed minimum water guidelines for irrigation to ensure flexibility and effective water allocation. Additionally, we suggest a set of regulatory measures to promote model transparency and robustness, certifying software that makes conscious and intelligent water allocation decisions, ultimately safeguarding agriculture from undue strain during droughts

A Self-Adaptive Penalty Method for Integrating Prior Knowledge Constraints into Neural ODEs

The continuous dynamics of natural systems has been effectively modelled using Neural Ordinary Differential Equations (Neural ODEs). However, for accurate and meaningful predictions, it is crucial that the models follow the underlying rules or laws that govern these systems. In this work, we propose a self-adaptive penalty algorithm for Neural ODEs to enable modelling of constrained natural systems. The proposed self-adaptive penalty function can dynamically adjust the penalty parameters. The explicit introduction of prior knowledge helps to increase the interpretability of Neural ODE -based models. We validate the proposed approach by modelling three natural systems with prior knowledge constraints: population growth, chemical reaction evolution, and damped harmonic oscillator motion. The numerical experiments and a comparison with other penalty Neural ODE approaches and \emph{vanilla} Neural ODE, demonstrate the effectiveness of the proposed self-adaptive penalty algorithm for Neural ODEs in modelling constrained natural systems. Moreover, the self-adaptive penalty approach provides more accurate and robust models with reliable and meaningful predictions

Numerical Simulation of the Production of Core-Shell Microparticles

Conventional methods that are commonly used for the preparation of microbubble delivery systems include sonication, high-shear emulsification, and membrane emulsification. However, these methods present significant disadvantages, namely, poor control over the particle size and distribution. To date, engineering core-shell microparticles remains a challenging task. Thus, there is a demand for new techniques that can enable control over the size, composition, stability, and uniformity of microparticles. Microfluidic techniques offer great advantages in the fabrication of microparticles over the conventional processes because they require mild and inert processing conditions. In this work, we present a numerical study based on the finite volume method, for the development of capsules by considering the rheological properties of three phases, air, a perfluorohexane (C6 F14) and a polymeric solution constituted of a solution of 0.25% w/v alginate. This methodology allows studying the stability and behavior of microparticles under different processing conditions

Fractional bioheat equation

In this work we develop a new mathematical model for the Pennes’ bioheat equation assuming a fractional time derivative of single order. A numerical method for the solu- tion of such equations is proposed, and, the suitability of the new model for modelling real physical problems is studied and discussedCOMPETE, FEDER and Fundação para a Ciência e a Tecnologia (the Portuguese Foundation for Science and Technology (FCT)) through Projects UID/CTM/50025/2013, PTDC/EME- MFE/113988/2009 and EXPL/CTM-POL/1299/2013. M. Rebelo acknowledge financial funding by the Portuguese Foundation for Science and Technology through the project PEstOE/MAT/UI0297/2013 (Centro de Matemática e Aplicacões

Recent Advances in Complex Fluids Modeling

In this chapter, we present a brief description of existing viscoelastic models, starting with the classical differential and integral models, and then focusing our attention on new models that take advantage of the enhanced properties of the Mittag-Leffler function (a generalization of the exponential function). The generalized models considered in this work are the fractional Kaye-Bernstein, Kearsley, Zapas (K-BKZ) integral model and the differential generalized exponential Phan-Thien and Tanner (PTT) model recently proposed by our research group. The integral model makes use of the relaxation function obtained from a step-strain applied to the fractional Maxwell model, and the differential model generalizes the familiar exponential Phan-Thien and Tanner constitutive equation by substituting the exponential function of the trace of the stress tensor by the Mittag-Leffler function. Since the differential model is based on local operators, it reduces the computational time needed to predict the flow behavior, and, it also allows a simpler description of complex fluids. Therefore, we explore the rheometric properties of this model and its ability (or limitations) in describing complex flows

Semi-analytical solutions for the poiseuille-couette flow of a generalised Phan-Thien-Tanner fluid

This work presents new analytical and semi-analytical solutions for the pure Couette and Poiseuille-Couette flows, described by the recently proposed (Ferras et al., A Generalised Phan-Thien-Tanner Model, JNNFM 2019) viscoelastic model, known as the generalised Phan-Thien-Tanner constitutive equation. This generalised version considers the Mittag-Leffler function instead of the classical linear or exponential functions of the trace of the stress tensor, and provides one or two new fitting constants in order to achieve additional fitting flexibility. The analytical solutions derived in this work allow a better understanding of the model, and therefore contribute to improve the modelling of complex materials, and will provide an interesting challenge to computational rheologists, to benchmarking and to code verification.This research was funded by FEDER through COMPETE2020-Programa Operacional Competitividade e Internacionalizacao (POCI) and by national funds through FCT-Fundacao para a Ciencia e a Tecnologia, I. P. through Projects PTDC/EMS-ENE/3362/2014, POCI-01-0145-FEDER-016665, UID-MAT-00013/2013, and UID/MAT/00297/2013 as well as grant number SFRH/BPD/100353/2014. This work was partially supported by the Fundacao para a Ciencia e a Tecnologia (Portuguese Foundation for Science and Technology) through the project UID/MAT/00297/2019 (Centro de Matematica e Aplicacoes)

Maker Club in Pre-School

The project allows pre-school children to develop the problematization of what they are learning and, in secondary school, students’ perspectives of cooperative in the development of scientific literacy. In this type of activity, children, with the help of high school students, deepen and consolidate behavioral values for life, thus enabling a positive change in their attitudes, in the way of believing, innovating, planning and persisting to conquer. Theactivities developed are accessible, both in approach and availability as well as in the cost of materials

Autoconcepto del adolescente de secundaria básica en Remedios, Cuba

El estudio realizado, derivado de la investigación “Programa psicoeducativo orientado a la disminución de conductas de riesgo sexual en adolescentes en la ciudad de Remedios”, de la Facultad de Psicología de la Universidad Central “Marta Abreu” de Las Villas, del 2011, fue de tipo descriptivo para caracterizar el autoconcepto de los adolescentes de la secundaria básica “Juan Pedro Carbó Serviá” del municipio de Remedios en la provincia de Villa Clara, Cuba; tuvo una muestra de 463 estudiantes entre 11 y 15 años. El autoconcepto se abordó en función de los indicadores autoconocimiento, vínculo afectivo y potencial regulador para las dimensiones apariencia física, familiar, social, intelectual, personal y sensación de control. A los adolescentes se les aplicaron escalas autovalorativas y un test sociométrico, y a docentes y familia se aplicaron escalas valorativas. Los resultados mostraron un nivel alto de desarrollo en la dimensión familiar del autoconcepto de los adolescentes estudiados y un predominio del nivel medio de desarrollo en las otras cinco dimensiones. Sólo se registran diferencias significativas según el género en la dimensión intelectual y en la de apariencia física

Numerical solution for diffusion equations with distributed order in time using a Chebyshev collocation method

In this work we present a new numerical method for the solution of the distributed order time fractional diffusion equation. The method is based on the approximation of the solution by a double Chebyshev truncated series, and the subsequent collocation of the resulting discretised system of equations at suitable collocation points. An error analysis is provided and a comparison with other methods used in the solution of this type of equation is also performed

Viscoelasticity: Mathematical Modelling, Numerical Simulations, and Experimental Work

Viscoelastic materials are abundant in nature and present in our daily lives [...