Diverse classes of constraints enable broader applicability of a linear programming-based dynamic metabolic modeling framework

Current metabolic modeling tools suffer from a variety of limitations, from scalability to simplifying assumptions, that preclude their use in many applications. We recently created a modeling framework, Linear Kinetics-Dynamic Flux Balance Analysis (LK-DFBA), that addresses a key gap: capturing metabolite dynamics and regulation while retaining a potentially scalable linear programming structure. Key to this framework’s success are the linear kinetics and regulatory constraints imposed on the system. However, while the linearity of these constraints reduces computational complexity, it may not accurately capture the behavior of many biochemical systems. Here, we developed three new classes of LK-DFBA constraints to better model interactions between metabolites and the reactions they regulate. We tested these new approaches on several synthetic and biological systems, and also performed the first-ever comparison of LK-DFBA predictions to experimental data. We found that no single constraint approach was optimal across all systems examined, and systems with the same topological structure but different parameters were often best modeled by different types of constraints. However, we did find that when genetic perturbations were implemented in the systems, the optimal constraint approach typically remained the same as for the wild-type regardless of the model topology or parameterization, indicating that just a single wild-type dataset could allow identification of the ideal constraint to enable model predictivity for a given system. These results suggest that the availability of multiple constraint approaches will allow LK-DFBA to model a wider range of metabolic systems.

Phonological Processes in Ekegusii Borrowing: A Constraint-based Approach

Phonological processes are at the heart of linguistic borrowing as it has varied phonological systems. It could be seen that the loan words entering the loan language from the source language can hardly be separated from the phonological process because they must be modified to suit the phonology of the loan language. This article analysed the phonological processes realized in Ekegusii borrowing from English using Optimality Theory’s constraint approach. Since this was a phonological study, descriptive linguistic fieldwork was used. The data used in this article was extracted from Mose’s doctoral study, whereby purposive sampling was used to obtain two hundred borrowed segments from the Ekegusii dictionary, then supplemented by introspection. Further, three adult native proficient Ekegusii speakers who were neither too young nor too old and had all their teeth were purposively sampled. The two hundred tokens were then subjected to the sampled speakers through interviews to realize the sound patterns in the Ekegusii borrowing process overtly. The findings revealed that Ekegusii phonological constraints defined the well-formedness of the loanwords by repairing the illicit structures. To fix, various phonological processes were realized. They included: epenthesis, deletion, devoicing/strengthening, voicing/ weakening, re-syllabification, substitution, monophthongization, and lenition. The article concludes that borrowing across languages (related or unrelated) reports similar if not the same phonological processes only that the processes attested in one language are a subset of the universally exhibited phonological processes.

Non-Pharmaceutical Stochastic Optimal Control Strategies to Mitigate the COVID-19 Spread

This paper proposes a stochastic non-linear model predictive controller to support policy-makers in determining robust optimal non-pharmaceutical strategies to tackle the COVID-19 pandemic waves. First, a time-varying <i>SIRCQTHE</i> epidemiological model is defined to get predictions on the pandemic dynamics. A stochastic model predictive control problem is then formulated to select the necessary control actions (i.e., restrictions on the mobility for different socio-economic categories) to minimize the socio-economic costs. In particular, considering the uncertainty characterizing this decision-making process, we ensure that the capacity of the healthcare system is not violated in accordance with a chance constraint approach. The effectiveness of the presented method in properly supporting the definition of diversified non-pharmaceutical strategies for tackling the COVID-19 spread is tested on the network of Italian regions using real data. The proposed approach can be easily extended to cope with other countries' characteristics and different levels of the spatial scale.<br><br><div><br></div><div>Postprint accepted for pubblication in <i>IEEE Transactions on Automation Science and Engineering</i> (T-ASE)</div><div><br></div><div><b>How to cite</b>: P. Scarabaggio, R. Carli, G. Cavone, N. Epicoco and M. Dotoli, (2021) "Non-Pharmaceutical Stochastic Optimal Control Strategies to Mitigate the COVID-19 Spread," in IEEE Transactions on Automation Science and Engineering.</div><div><br></div><div>DOI: http://doi.org/10.1109/TASE.2021.3111338<br><br></div>

Topology Optimization for Additively Manufactured Self-Supporting Axisymmetric Structures

This paper discusses the design of axisymmetric structures with self-supporting features that can be additively manufactured without requiring internal support structures. This is motivated by wire-fed additive manufacturing processes, many of which can fabricate designs with enclosed pores that inherently exist in many axisymmetric structures, such as double walled pressure vessels. Although enclosed pores are possible, features that rise at shallow angles from the build plate typically cannot be fabricated without the use of support structures, which require removal and thus are unfavorable in such applications. In this paper, an overhang constraint is applied to ensure that all designed features rise at a designer-prescribed self-supporting angle to eliminate the need for such support structures. This is achieved by coupling the projection-based overhang constraint approach with topology optimization and axisymmetric finite elements whose stiffness is interpolated using Solid Isotropic Material with Penalization (SIMP). Gradients are computed with the adjoint method and the Method of Moving Asymptotes (MMA) is employed as the gradient-based optimizer. Two numerical examples related to a canonical pressure vessel and an optical mirror support structure are used to demonstrate the approach. Solutions are shown to satisfy minimum feature size requirements and designer-prescribed (process dependent) overhang constraint angles, while providing clear and crisp representations of topology. As observed in past works on overhang constraints, a clear trade-off is illustrated between the magnitude of the overhang constraint angle and the structural performance (mass or stiffness), with more strict requirements producing designs with lower performance.

Predicting Stock Return with Economic Constraint: Can Interquartile Range Truncate the Outliers?

We find that imposing economic constraint on stock return forecasts based on the Interquartile Range of equity premium can significantly strengthen predictive performance. Specifically, we construct a judgment mechanism that truncates the outliers in forecasts of stock return. We prove that our constraint approach can realize more accurate predictive information relative to the unconstraint approach from the perspective of statistics and economics. In addition, the new constraint approach can effectively defeat CT constraint and CDA strategy. The three mixed models we proposed can further enhance the accuracy of prediction, especially the mixed model combined with our constraint approach. Finally, utilizing our new constraint approach can help investors obtain considerable economic gains. With the application of extension and robustness analysis, our results are robust.

A hierarchical constraint approach for dynamic modeling and trajectory tracking control of a mobile robot

The dynamic modeling and trajectory tracking control of a mobile robot is handled by a hierarchical constraint approach in this study. When the wheeled mobile robot with complex generalized coordinates has structural constraints and motion constraints, the number of constraints is large and the properties of them are different. Therefore, it is difficult to get the dynamic model and trajectory tracking control force of the wheeled mobile robot at the same time. To solve the aforementioned problem, a creative hierarchical constraint approach based on the Udwadia–Kalaba theory is proposed. In this approach, constraints are classified into two levels, structural constraints are the first level and motion constraints are the second level. In the second level constraint, arbitrary initial conditions may cause the trajectory to diverge. Thus, we propose the asymptotic convergence criterion to deal with it. Then, the analytical dynamic equation and trajectory tracking control force of the wheeled mobile robot can be obtained simultaneously. To verify the effectiveness and accuracy of this methodology, a numerical simulation of a three-wheeled mobile robot is carried out.