Article
Automation & Control Systems
Jingxin Zhang, Maoyin Chen, Xia Hong
Summary: Industrial processes operate under multiple modes, and a global monitoring approach requires complete data from all potential modes. This article proposes an efficient algorithm for multimode nonlinear dynamic process monitoring, which builds a single monitoring model with continual learning ability. The proposed method selects representative data from each mode based on cosine similarity and preprocesses data from all existing modes to build a single multimode monitoring model. The method can handle nonlinearity and has a regularization term to avoid overfitting. The effectiveness of the proposed approach is demonstrated by experiments on a continuous stirred tank heater and a practical industrial system.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Information Systems
Jingru Ren, Wenming Zhu
Summary: This paper proposes a two-stage local search strategy, called dual scatter search strategy, for generating automated test cases for path coverage. Experimental studies on twelve benchmark programs demonstrate that this strategy achieves the highest path coverage with the fewest test cases and running time.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2023)
Article
Engineering, Chemical
Enzhi Liang, Zhihong Yuan
Summary: In this paper, an integrated framework for the robust dynamic optimization of nonlinear chemical processes under measurable and unmeasurable uncertainties is proposed. The framework utilizes an affine decision rule and a linearization technique to address the computational challenges and is compared with state-of-the-art approaches. The advantages and applicability of the framework are demonstrated through illustrative and industrial examples.
Article
Computer Science, Artificial Intelligence
Havva Gul Kocer, Sait Ali Uymaz
Summary: In this paper, a novel local search method named GRGLS is proposed for large-scale optimization problems. The experiments show that the proposed method performs well in various functions, especially excelling in overlapping and non-separable functions.
Article
Computer Science, Interdisciplinary Applications
Shanbin Lu, Zhaobin Zhang, Huiqiang Guo, Gyung-Jin Park, Wenjie Zuo
Summary: This paper presents a method for obtaining explicit geometry structure in nonlinear dynamic topology optimization using moving morphable components method and equivalent static loads method. By converting the nonlinear dynamic problem into a linear static problem and introducing transformation variables, the optimization process is made more efficient.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Engineering, Environmental
S. N. Poojitha, V Jothiprakash, Bellie Sivakumar
Summary: The study proposes a chaos-directed genetic algorithm (CDGA) for optimizing the design of water distribution networks (WDNs). By introducing two novel frameworks and exploring the influence of high-dimensionality chaotic systems, the CDGA models outperform traditional genetic algorithms (GA) and other optimization techniques in terms of search efficacy.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2022)
Article
Computer Science, Artificial Intelligence
Yu-Qin Chen, Yu Chen, Chee-Kong Lee, Shengyu Zhang, Chang-Yu Hsieh
Summary: This study proposes a method for designing quantum annealing schedules, based on Monte Carlo tree search algorithm and neural networks. The experiments demonstrate that both MCTS and QZero algorithms perform well in finding effective annealing schedules, even with short annealing time for 3-SAT examples. Compared to other reinforcement learning algorithms, MCTS and QZero are more efficient in designing annealing schedules.
NATURE MACHINE INTELLIGENCE
(2022)
Article
Engineering, Chemical
Yuedong Zhang, Yuanbin Mo
Summary: The modified sailfish optimizer (MSFO) proposed in this paper is used to solve chemical dynamic optimization problems. By introducing chaotic mapping strategy, adaptive linear reduction strategy, and modification of position updating formula, its exploration and exploitation ability is enhanced to avoid the loss of population diversity and premature phenomenon of the algorithm.
Article
Multidisciplinary Sciences
Zhicheng Yan, Qibing Jin, Yang Zhang, Zeyu Wang, Ziming Li
Summary: This paper proposes a multi-objective harris hawk optimization algorithm based on blank angle region enhanced search (BARESMOHHO) to address the issues of low precision, low search efficiency, and being easy to fall into local optimization. The algorithm initializes the population using chaotic mapping, adjusts the classification level to find low-density regions faster, symmetrically distributes the number of archives at different levels for uniform distribution of individuals in the target space, and strengthens the search for non-individual regions in the division process. The effectiveness of the algorithm is verified through comparisons with known classical functions on test functions.
Article
Engineering, Chemical
Jingjing Guo, Wenli Du, Qun Wu, Zhencheng Ye
Summary: This work proposes an optimization algorithm based on IE and RS to address common dynamic optimization problems in the chemical industry, combining the advantages of heuristic algorithms and iterative dynamic optimization to ensure both fast convergence and effectiveness of the algorithm.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2021)
Article
Multidisciplinary Sciences
Vasileios Charilogis, Ioannis Tsoulos, Alexandros Tzallas, Nikolaos Anastasopoulos
Summary: The modified controlled random search method is designed for estimating global minimum of multidimensional symmetric and asymmetric functional problems, incorporating a new sampling method, termination rule and periodic local search optimization. Comparison with the original method using benchmark functions showed improvements in performance.
Article
Computer Science, Artificial Intelligence
Pu Sun, Hao Liu, Yong Zhang, Qingyao Meng, Liangping Tu, Jian Zhao
Summary: The DOLHCLASO algorithm addresses the issue of premature convergence in ASO by introducing dynamic opposite learning and heterogeneous comprehensive learning. Experimental results demonstrate that DOLHCLASO outperforms other selected optimizers in the CEC2017 benchmark functions and real-world engineering cases.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Jing Lian, Weiwei Ren, Dongfang Yang, Linhui Li, Fengning Yu
Summary: This article focuses on the problem of trajectory planning for autonomous valet parking in complex environments. It proposes an enhanced hybrid A* (EHA) algorithm to address the challenge of finding proper initial guesses. The EHA algorithm includes four steps: obtaining a global coarse trajectory, constructing driving corridors, extracting boundary points, and generating a feasible initial guess. The experimental results demonstrate the effectiveness and robustness of the proposed method.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2023)
Article
Computer Science, Interdisciplinary Applications
Florian Joseph Baader, Philipp Althaus, Andre Bardow, Manuel Dahmen
Summary: Volatile electricity prices make demand response attractive for processes that can modulate their production rate. However, scheduling optimization problems often cannot be solved in real time when nonlinear dynamic processes must be scheduled simultaneously with their local multi-energy system. This work extends dynamic ramping constraints to flat multi-input multi-output processes by a coordinate transformation, allowing for a mixed-integer linear formulation that guarantees feasible operation.
COMPUTERS & CHEMICAL ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
Andre M. Garcia, Leonardo H. Macedo, Ruben Romero
Summary: This article presents a specialized scatter search algorithm to solve the optimal transmission switching problem considering voltage control, and its efficiency is validated through tests.
ELECTRIC POWER SYSTEMS RESEARCH
(2024)
Article
Automation & Control Systems
Gemma Massonis, Julio R. Banga, Alejandro F. Villaverde
Summary: Mechanistic dynamic models of biological systems often suffer from over-parameterization, resulting in nonidentifiability and nonobservability. AutoRepar is a methodology that automatically corrects these structural deficiencies, producing reparameterized models with improved identifiability and observability. This approach increases the applicability of mechanistic models, providing reliable information about their parameters and dynamics.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Chemistry, Applied
Gerardo Gonzalez-Tejedor, Alberto Garre, Jose A. Egea, A. Aznar, Francisco Artes-Hernandez, Pablo S. Fernandez
Summary: The inactivation kinetics of Listeria monocytogenes during High Hydrostatic Pressure treatments were investigated, and the effects on quality attributes were monitored. The study found that increasing pressure intensity led to faster microbial inactivation, while mostly unaffected the quality attributes except for the reduction in vitamin C content.
FOOD SCIENCE AND TECHNOLOGY INTERNATIONAL
(2023)
Article
Biochemistry & Molecular Biology
Diego Hernandez-Prieto, Pablo S. S. Fernandez, Vicente Agullo, Cristina Garcia-Viguera, Jose A. Egea
Summary: The present study examines the impact of a beverage containing citrus and maqui with various sweeteners on male and female consumers. The beverages were developed and tested as a source of polyphenols in an earlier study. Plasma samples were collected before and after two months of daily consumption, and metabolomics techniques were used to measure bioactive-compound levels. Advanced versions of ANOVA and clustering analysis were employed to determine the effects of sex and sweetener factors on these compounds. Machine learning techniques were also applied to improve the results. The findings demonstrate sex-specific regulation of certain compounds, such as caffeic acid and 3,4-dihydroxyphenylacetic acid for men, and trans ferulic acid (TFA) or naringenin glucuronide for women. Sweeteners, such as stevia for women or sucrose for men, were also observed to have an impact on the regulation of these compounds.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Environmental Sciences
Eduardo Fernandez, Hajar Mojahid, Erica Fadon, Javier Rodrigo, David A. Ruiz, Jose Egea, Mehdi Ben Mimoun, Ossama Kodad, Adnane El Yaacoubi, Mohamed Ghrab, Jose Egea, Haifa Benmoussa, Nadia Borgini, Olfa Elloumi, Eike Luedeling
Summary: To assess agroclimatic conditions for cultivating temperate trees, we studied winter chill in the Mediterranean region, and collected expert knowledge about climate change impacts and risks. Results showed significant chill losses in northern African growing regions, which likely caused irregular and delayed bloom. These regions, along with southern Europe, may lose up to 30 Chill Portions by 2050 under a moderate warming scenario. Experts foresee increasing risks of spring frost, exacerbated bloom-related problems, and more frequent heat waves.
REGIONAL ENVIRONMENTAL CHANGE
(2023)
Article
Biotechnology & Applied Microbiology
Artai R. Moimenta, David Henriques, Romain Minebois, Amparo Querol, Eva Balsa-Canto
Summary: Saccharomyces non-cerevisiae yeasts are being increasingly studied for their potential to reduce ethanol content and enhance aroma profiles in wine fermentation. This study develops a continuous model that considers the physiological status of yeast during fermentation, accurately predicting biomass and primary and secondary metabolite dynamics. The model is also used to explore different process designs, highlighting the impact of nitrogen addition on wine aromas. This research emphasizes the importance of incorporating yeast physiology into fermentation modeling and provides a new approach to automating process design.
MICROBIAL BIOTECHNOLOGY
(2023)
Editorial Material
Food Science & Technology
Jose A. Egea, Miriam R. Garcia, Carlos Vilas
Article
Biotechnology & Applied Microbiology
William T. Scott, David Henriques, Eddy J. Smid, Richard A. Notebaart, Eva Balsa-Canto
Summary: Fermentation using Saccharomyces cerevisiae has been used for thousands of years to produce alcoholic beverages and bread. Recently, this yeast has been utilized for manufacturing specific metabolites for various industries. The latest metabolic model of S. cerevisiae has revealed both conserved and species-specific mechanisms related to aroma production in wine yeasts, providing valuable insights for optimizing their behavior in industrial settings.
BIOTECHNOLOGY AND BIOENGINEERING
(2023)
Article
Biochemical Research Methods
Carlos Sequeiros, Irene Otero-Muras, Carlos Vazquez, Julio R. Banga
Summary: Mechanistic dynamic models are important for understanding biomolecular networks and biological systems. Stochastic dynamic models should be used when dealing with low copy numbers and biochemical stochasticity. This article presents a novel strategy for parameter estimation in stochastic dynamic models, employing global optimization and stochastic simulation techniques.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2023)
Article
Biochemical Research Methods
Alejandro F. Villaverde, Elba Raimundez, Jan Hasenauer, Julio R. Banga
Summary: Biological processes are often modelled using ordinary differential equations, and the unknown parameters of these models are estimated by optimizing the fit of model simulation and experimental data. However, accurately estimating the prediction uncertainties due to the nonlinear dependence of model characteristics on parameters is challenging. To address this, we applied four state-of-the-art methods for uncertainty quantification to four case studies of different computational complexities, revealing the trade-offs between their applicability and statistical interpretability. Our results provide guidelines for choosing the most appropriate technique for a given problem and applying it successfully.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2023)
Article
Microbiology
David Henriques, Romain Minebois, David dos Santos, Eladio Barrio, Amparo Querol, Eva Balsa-Canto
Summary: Nonconventional yeasts offer new metabolic pathways for producing industrially relevant compounds and tolerating specific stressors like cold temperatures. However, the mechanisms behind the cold tolerance of S. kudriavzevii and its sympatric relationship with S. cerevisiae in Mediterranean oaks are not well understood.
MICROBIOLOGY SPECTRUM
(2023)
Article
Biochemistry & Molecular Biology
Diego Hernandez-Prieto, Alberto Garre, Vicente Agullo, Cristina A. Garcia-Viguera, Jose A. Egea
Summary: Metabolic diseases have been linked to excessive consumption of high-sugar content beverages. To address this, there has been an increased demand for plant-based formulations with health-promoting properties. A longitudinal trial with 140 volunteers was conducted to assess the bioavailability of (poly)phenols in a maqui-citrus beverage, and it was discovered that the sex of the volunteer and the type of sweetener added to the beverage had an impact on the bioavailability of the (poly)phenol metabolites. Clustering analysis also revealed patterns in the distribution of metabolites based on sex and/or sweeteners. These findings highlight the potential of stevia as a bioavailability enhancer and demonstrate that sex plays a role in the metabolism of (poly)phenols.
Article
Plant Sciences
Cristian Perez-Caselles, Lorenzo Burgos, Inmaculada Sanchez-Balibrea, Jose A. Egea, Lydia Faize, Marina Martin-Valmaseda, Nina Bogdanchikova, Alexey Pestryakov, Nuria Alburquerque
Summary: The effects of silver nanoparticles on in vitro growth and leaf ion composition of 'Canino' and 'Mirlo Rojo' cultivars were studied. It was found that the use of silver nanoparticles in a liquid medium improved plant proliferation and biomass production, while its use in a semisolid medium decreased productivity.
Article
Biochemical Research Methods
Ahmed Taha, Mauricio Paton, David Penas, Julio Banga, Jorge Rodriguez
Summary: In this study, a method is developed to evaluate the feasibility of alternative metabolic pathways in microbes by optimizing the energy yield and driving forces of metabolic intermediates. The method uses thermodynamic principles and multi-objective optimization to consider different pathway variants. Other constraints, such as the balance of conserved components, are also taken into account. The method transforms the maximum energy yield problem into a multi-objective mixed-integer linear optimization problem and solves it using the epsilon-constraint method. The methodology is applied to analyze different pathways in propionate oxidation and CO2 fixation by microbes.
PLOS COMPUTATIONAL BIOLOGY
(2023)
Article
Agriculture, Multidisciplinary
Gabriela L. Salazar-Orbea, Rocio Garcia-Villalba, Maria J. Bernal, Alberto Hernandez-Jimenez, Jose A. Egea, Francisco A. Tomas-Barberan, Luis M. Sanchez-Siles
Summary: This research focused on how storage conditions and processing techniques affect the composition of nutrients, bioactive compounds, and sensory attributes in strawberry and apple purees. The study found that storage conditions had a stronger impact on phenolic compounds in strawberry puree, while initial processing techniques had a greater influence on apple puree. The stability of polyphenols varied between fruits during storage, and selecting the optimal storage conditions is crucial for maintaining the polyphenol content in sensitive fruits like strawberries.
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
(2023)
Article
Biochemical Research Methods
Gemma Massonis, Alejandro F. Villaverde, Julio R. Banga
Summary: MotivationDynamic mechanistic modelling in systems biology has been hindered by complexity and variability, as well as uncertain and sparse experimental measurements. Ensemble modelling has been introduced to mitigate these issues, but is unreliable for predicting non-observable states. In this study, the authors present a strategy to assess and improve the reliability of model ensembles, using a diversity-enforcing technique combined with identifiability and observability analysis. They demonstrate the effectiveness of their approach with models of glucose regulation, cell division, circadian oscillations, and the JAK-STAT signalling pathway.
