Formulation Of Model Research Articles

A strategy to what end? “The strategy of model building in population biology” in its programmatic context

Abstract“The Strategy of Model Building in Population Biology” published by Richard Levins in 1966 has been cited over 2500 times. For a paper concerned with modeling approaches in population biology a surprisingly large part of the attention. The Strategy received comes from history and philosophy of biology, and specifically from accounts on model and model formulation. The Strategy is an unusual paper; it presents neither new data nor a new formal model; at times it reads like a manifesto for some modeling approach, without specifying which broader program that approach intends to support. When these peculiarities of The Strategy are even mentioned, the philosophical literature tends to explain them away by invoking Levins’ Marxist commitments. In contrast, I argue that those peculiarities can be explained by examining the programmatic purpose of the paper; starting from his doctoral work, Levins was trying to establish a research program meant to account for the relations between fitness and environment in different terms than the prevalent lock-and-key view. My paper brings that program back to the discussion, explains its relation to competing approaches and examines Levins’ approach to modeling in light of that context

Finding Critical Factors for Developing Dynamic Models to Optimize Greenhouse Solar Dryer’s Environmental Conditions

This paper is focused on the formulation of a mathematical model for greenhouse solar dryer systems in the context of determining the principal drivers of efficiency of the solar dryer. The model was built by evaluating the correlation coefficients of each term and only those terms which had high levels of significance were retained. To test this model, experiments were replicated with measurements being taken in the different sections of the greenhouse to provide a large spectrum of the environmental conditions involved. The values of the technical coefficients are predicated on internal air temperature, humidity ratio and weight of the product with fixed scales, avoiding sophisticated complex models prone to overfitting. By using terms with high correlation, the model is less likely to be affected by outliers and total correlation or cross correlation is low, thereby making the model practical. The outcomes of this research, therefore, offer a scientifically viable and a practical approach to enhancing drying processes in greenhouse solar dryer systems.

Multilinear regression model for predicting the ultimate load of slender circular CFDST columns subjected to concentric and eccentric loading

AbstractThis paper presents a novel approach to predict the ultimate load of slender circular concrete‐filled double skin tubular (CFDST) columns subjected to concentric and eccentric loading. The proposed approach was developed using a multilinear regression model through analyzing a database containing 165 CFDST column configurations. The data set was obtained by varying the magnitude of the parameters to determine its effect on the ultimate load using FE analysis. The variables considered in the model formulation are concrete strength, steel tube strengths, tube diameters, tube thicknesses, load eccentricity, column curvature, and column length. The accuracy and efficiency of the proposed models were validated with previous experimental investigations. The results demonstrate that the proposed models provide a practical, simple, and efficient approach to predict the ultimate load of slender circular CFDST columns subjected to concentric and eccentric loading. When compared to existing experimental work on slender circular CFDST columns subjected to concentric and eccentric loading, the proposed model over predicts the ultimate load by a maximum of 6%.

Sport spectator well-being: a scoping review

ABSTRACT A clear understanding of sport consumer well-being is central to enriching research on the interaction between sport organizations and consumers, and more tangibly, to advancing public policy. This research offers a scoping review of existing studies on the well-being of sport spectators, resulting in the formulation of a Sport Spectator Well-being Process Model designed to direct future research endeavors. The review includes 76 peer-reviewed articles comprising reviews, qualitative and quantitative studies. A dual approach of frequency and thematic analysis was utilized to synthesize the findings. The frequency analysis highlighted an increasing trend in relevant publications over time, and the thematic analysis informed the development of a conceptual model of the four key stages of the sport spectator well-being process. The review also identified three significant research gaps: (1) the narrow scope of research contexts, (2) a limited range of theoretical frameworks employed and (3) challenges in research methodology. The findings significantly contribute to the transformative sport service research by integrating positive psychology concepts into the discourse on sport spectator well-being. The conceptual model is vital for researchers exploring the intricate relationship between sport spectatorship and spectator well-being, ensuring a comprehensive understanding of this significant topic.

Issues Associated With the Formulation of a Small Area Model for Estimation of State-Level Crime Victimization Rates

Subnational estimation is an important and challenging problem in the context of the National Crime Victimization Survey (NCVS). Direct estimates for subnational domains are often unreliable due to small sample sizes. Model-based procedures have potential to improve upon direct estimators. However, model-based estimation presents several new challenges. One must identify suitable covariates, and an appropriate model form must be specified. This article discusses issues associated with the formulation of a small area model for production of state-level estimates of crime victimization rates. An analysis of direct estimates and covariates motivates the development of a Bayesian multivariate model. A model in the original scale is compared to a model in the log scale. Efficiency gains from the model relative to the direct estimators are examined. One challenge is that direct estimates can equal zero. Two ways of handling zero direct estimates are discussed.

Development of Idaea inquinata (Lepidoptera Geometridae) at different constant temperatures and relative humidities under controlled conditions

The rusty wave moth Idaea inquinata is an insect pest that infests dried herbs, above all when stored in warehouses. Infestations were historically localised, but the recent climatic change might increase the incidence of this pest in many areas of north Italy. The artificial regulation of the environmental conditions of warehouses is one of the most common techniques to control pests, often combined with thermal treatments just after the introduction of the stocks. The optimisation of the warehouse conditions, however, requires a deep knowledge on how the species react to variations in temperature and relative humidities. This information is to date missing for I. inquinata and this work aimed to fill this gap in knowledge. The life tables at 35% and 70% RH, and at different constant temperatures were obtained for the egg, larval, and pupal stages by combining datasets provided by 20 years of continuous rearing of this species. A second part of the study, instead, concerned the estimation of the parameters of the temperature-dependent development rate functions, laying the foundations for further formulations of mathematical models to be applied in decision support systems. Life tables showed that conditions of low relative humidities and low temperatures are a good compromise that slows down the development time of the preimaginal stages. The upper thermal limit for the development of this species, instead, is around 40 °C, a threshold that can be considered for further thermal treatments to disinfest warehouses before the introduction of pest-free stocks or as a controlling action in case of infestations.

Epistemic commitments have no “Off” button: on the embodiment of commitments by way of model formulation

The current paper examines how a commitment to a principle, adhered to by an individual agent, becomes an accepted standard of an epistemic community. Addressing this question requires three steps: first, to define the terms used throughout the paper, and especially the characteristics of commitments to a principle. The second step is to find a mechanism through which such epistemic commitments are introduced to an epistemic community and in certain cases are adopted as the standard by the community. While there could be several such mechanisms, the current paper focuses on the practice of model formulation. The third step is to demonstrate the analytical framework developed in the first two steps in a case study. The case study chosen for this paper is the unique approach to feedback analysis adopted by the ecologist and population geneticist Richard Levins. In what follows I will show that part of the features that made Levins’ approach unique was his Marxist commitments, and his attempt to embody those commitments in feedback analysis by formally representing them as modeling assumptions.

Basic curvature & the Atiyah cocycle in gauge theory

Abstract Motivated from target space covariant formulations of topological sigma models and from a graded-geometric approach to higher gauge theory, we study connections on Lie and Courant algebroids and on their description as differential graded (dg) manifolds. We revisit the notion of basic curvature for a connection on a Lie algebroid, which measures its compatibility with the Lie bracket and it appears in the BV-BRST differential of 2D gauge theories such as (twisted) Poisson and Dirac sigma models. We define a basic curvature tensor for connections on Courant algebroids and we show that in the description of a Courant algebroid as a QP2 manifold it appears naturally as part of the homological vector field together with the Gualtieri torsion of an induced generalised connection. Furthermore, we consider connections on dg manifolds and revisit the structure of gauge transformations in the graded-geometric approach to higher gauge theories from a manifestly covariant perspective. We argue that it is governed by the brackets of a Kapranov L ∞ [ 1 ] algebra, whose binary bracket is given by the Atiyah cocycle that measures the compatibility of the connection with the homological vector field. We also revisit some aspects of the derived bracket construction and show how to extend it to connections and tensors.

Investigating Model Form Error Estimation for Sparse Data

Computational simulations of dynamical systems involve the use of mathematical models and algorithms to mimic and analyze complex real-world phenomena. By leveraging computational power, simulations enable researchers to explore and understand systems that are otherwise challenging to study experimentally. They offer a cost-effective and efficient means to predict and analyze the behavior of physical, biological, and social systems. However, model form error arises in computational simulations from simplifications, assumptions, and limitations inherent in the mathematical model formulation. Several methods for addressing model form error have been proposed in the literature, but their robustness in the face of challenges inherent to real-world systems has not been thoroughly investigated. In this work, a data assimilation-based approach for model form error estimation is investigated in the presence of sparse observation data. Including physics-based domain knowledge to improve estimation performance is also explored. The Lotka-Volterra equations are employed as a simple computational simulation for demonstration.

Dynamic Formulation of the Double Multiple Stream Tube Model of Offshore Vertical Axis Wind Turbines

Abstract The paper proposes a novel algorithm to simulate Vertical Axis Wind Turbines in floating motion based on a low-fidelity approach. The conventional Double Multiple Stream Tube Model is formulated as a steady state model to deal with the inherent unsteady aerodynamics of VAWTs. The Double Multiple Stream Tube Model makes use of an average contribution of the blade passages over a revolution to solve the Blade Element Momentum equation. The model reduces the dependence of the solution (the induction field) to a space variable. Floating Vertical Axis Wind Turbines undergoes a variation of aerodynamic quantities according to wave periods, also different from the rotor period. This paper provides a new formulation of the Double Multiple Stream Tube Model to solve the turbine rotation in time and space, introducing the variation of the platform velocity and a revised approach to the downstream actuator disc. The most impactful parameter is found to be the wave frequency: wave periods at full-scale are lower than the ones of the turbine rotor, featuring optimal operating points at low tip speed ratios. The increase of the wave frequency highlights the differences of the average torque prediction for a single blade up to 10% between the unsteady and the standard formulation. In this context, the development of fast low-fidelity computational tools play a key role in the assessment of the preliminary designs of Floating Offshore Vertical Axis Wind Turbines and it will be used to optimise the aerodynamic design of the laboratory scaled model under surge motion.

Subsurface Sediment Transport in the Shallow Vadose Zone of Fine‐Textured Soils With Heterogenous Preferential Flows

ABSTRACTSubsurface sediment transport in tile‐drained landscapes occurs through macropores; however, little is known regarding how heterogeneous preferential flows influence fluxes. We performed laboratory rainfall simulations on 10 intact core lysimeters from a tile‐drained field in Indiana, USA to study the impacts of surface and subsurface erosion on sediment leachate in heterogeneous preferential flow paths. Seven rainfall simulations were conducted to assess the impact of rainfall intensity on the leachate of surface eroded sediments (three events), and the impact of antecedent conditions on subsurface eroded sediments (four events). Cumulative sediment yield, linear mixed effects modelling, and hysteresis analyses were performed for all events. Results were presented in a series of four case studies. Results showed that surface sediment leachate concentration and yield were tightly linked to the filtration capacity of lysimeters, with more than 2/3rd of sediment originating from a single lysimeter, despite similar flow leachate volumes from each. Rainfall intensity significantly impacted the transport of surface eroded sediment at the highest intensity. Subsurface sediment erosion from undisturbed macropores was low compared to surface soils, but we found contrasting controls on sediment concentrations at low and high antecedent moistures that were equally important to sediment leachate yields. Disturbed macropores produced comparable sediment yields to surface erosion and behaved similarly to soil pipes in terms of erosion mechanics. Hysteresis results generally highlighted contrasting results for surface and subsurface sources but suggest that the prominence of slow flow, low‐concentration leachate sources can alter the interpretation of results in field‐scale applications. Our findings underscore an array of processes and pathways for sediment transport in the shallow vadose zone, and results will be useful for evaluating new model formulations.

Transport and competitive interfacial adsorption of PFOA and PFOS in unsaturated porous media: Experiments and modeling

Among emerging contaminants, per- and polyfluoroalkyl substances (PFAS) have captured public attention based upon their environmental ubiquity and potential risks to human health. Due to their typical surface release conditions and amphiphilic properties, PFAS tend to sorb to soil and accumulate at the air-water interface within the vadose zone. These processes can result in substantial plume attenuation. Although there is a growing body of literature on vadose zone transport, few studies have explored PFAS mixture transport, particularly under conditions where nonlinear sorption processes are important. The present study aims to advance our understanding of PFAS transport in variably saturated porous media through integration of experiments and mathematical modeling. Experiments include batch studies to quantify sorption to the solid phase, interfacial tension (IFT) measurements to estimate adsorption at the air-water interface (AWI), and column studies with F-70 Ottawa sand at 100 % and ca. 50 % water saturation to explore transport mechanisms. Employed PFAS solutions encompass individual solutes and binary mixtures of perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) at concentration levels spanning four orders of magnitude to assess competitive and nonlinear sorption at the AWI. Observations demonstrate that concentration levels and competitive effects substantially influence PFAS transport in unsaturated systems. In the presence of PFOS, PFOA experienced less retention than would be anticipated based on single-solute behavior, and effluent breakthrough curves exhibited chromatographic peaking. The presented mathematical model for simultaneous flow and transport of PFAS was able to capture experimental observations with a consistent set of parameters and minimal curve fitting. These results demonstrate the robustness of the model formulation that included rate-limited interfacial mass transfer, an extended Langmuir-Szyszkowski model for adsorption at the AWI, and a scaled Leverett thermodynamic model to predict the AWI specific area. Overall, the results of this work underscore the importance of the AWI in PFAS transport and highlight the relevance of competition effects in adsorption formulations.

Triple junction benchmark for multiphase-field models combining capillary and bulk driving forces

Abstract A benchmark problem is formulated which is well suited for the validation of mesoscopic phase-field models for grain-boundary migration in polycrystals. First, an analytical steady-state solution of the sharp moving boundary problem is derived for a symmetric lamellar structure, which is valid for arbitrary bulk driving forces and triple junction angles. Characteristic quantities are identified to reduce the parameter space which in turn allows a systematic comparison of simulations and analytical results. Various multiphase-field (MPF) formulations are compared which approximate the sharp interface problem in terms of a diffuse regularization. An interfacial thickness convergence study reveals that the model error is largely dependent on the ratio of bulk to interfacial stabilizing force as well as the underlying model formulation. An additional grid convergence study highlights the efficiency of a more advanced discretization scheme. The results can be used to guide the selection of appropriate models and to estimate the interface thickness and spatial resolution required to achieve a given accuracy target. The post-processing framework consists of a fully automated determination of well-defined metrics from the phase field simulation data, eliminating human bias and facilitating reproducibility. The corresponding code is made openly available to assist the materials science and engineering community in validating MPF, multi-order parameter and similar model developments. We believe that this work provides a reliable benchmark procedure to better understand the potentials and limitations of current multiphase-field models as well as alternative approaches.

Circularity assessment of product-service systems using system dynamics modeling

Product-Service Systems (PSS) show the potential to implement the principles of a circular economy based on their characteristics, such as the use of an extended value network or the access of the PSS provider after distribution. PSS research shows that PSS are not inherently circular but must be designed specifically towards circularity. This requires an assessment method that can quantify the dimensions of circularity.In this paper, an assessment method based on system dynamics (SD) modeling is presented that allows the use of raw materials and the generation of waste to be evaluated in the context of PSS. The SD model is based on a conceptual integration of circular economy strategies into the lifecycle of PSS. The model formulation is described in detail and validated with several tests. The capabilities of the assessment approach are presented in an application scenario. The results show that SD modeling can be used for circularity assessment and can possibly serve as a starting point to enhance circularity.

Hydro-thermal Power Reserve Allocation Under Outage Uncertainty

In recent decades, the energy sector, namely energy markets have proved to be changing considerably. Most of these changes result in increasing volatility related to global political and environmental factors. This volatility affects all entities operating in the power sector. This paper focuses on the power plant operator’s perspective. First, the global context of the power sector is discussed and the power plant operator’s role is reviewed. Further, the problem of power reserve is discussed revealing the motivations of the presented work. The central contribution of this work lies in the formulation and development of a stochastic model of power reserve coupled with a mixed-integer programming scheduling model. In the results section, we show that the developed model allocates power reserve in an optimal way respecting the technical and economic parameters of the power plants as well as handling the stochastic nature of the power reserve allocation problem by minimizing the mean value of the sum of penalty for not delivering contracted power and lost opportunity.

Hidden zeros for particle/string amplitudes and the unity of colored scalars, pions and gluons

Recent years have seen the emergence of a new understanding of scattering amplitudes in the simplest theory of colored scalar particles — the Tr(ϕ3) theory — based on combinatorial and geometric ideas in the kinematic space of scattering data. In this paper we report a surprise: far from the toy model it appears to be, the “stringy” Tr(ϕ3) amplitudes secretly contains the scattering amplitudes for pions, as well as non-supersymmetric gluons, in any number of dimensions. The amplitudes for the different theories are given by one and the same function, related by a simple shift of the kinematics. This discovery was spurred by another fundamental observation: the tree-level Tr(ϕ3) field theory amplitudes have a hidden pattern of zeros when a special set of non-planar Mandelstam invariants is set to zero. These zeros are not manifest in Feynman diagrams but are made obvious by the connection of these amplitudes to the new understanding of associahedra arising from “causal diamonds” in kinematic space. Furthermore, near these zeros, the amplitudes simplify, by factoring into a non-trivial product of smaller amplitudes. Remarkably the amplitudes for pions and gluons are observed to also vanish in the same kinematical locus. These properties for Tr(ϕ3) amplitudes hold and further generalize to the “stringy” Tr(ϕ3) amplitudes. The “kinematic causal diamond” picture suggests a unique shift of the kinematic data that preserves the zeros, and this shift is precisely the one that unifies colored scalars, pions, and gluons into a single object. We will focus in this paper on explaining the hidden zeros and factorization properties and the connection between all the colored theories, working for simplicity at tree level. Subsequent works will describe this new formulation for the Non-linear Sigma Model and non-supersymmetric Yang-Mills theory, at all loop orders.

A general Bayesian algorithm for the autonomous alignment of beamlines.

Autonomous methods to align beamlines can decrease the amount of time spent on diagnostics, and also uncover better global optima leading to better beam quality. The alignment of these beamlines is a high-dimensional expensive-to-sample optimization problem involving the simultaneous treatment of many optical elements with correlated and nonlinear dynamics. Bayesian optimization is a strategy of efficient global optimization that has proved successful in similar regimes in a wide variety of beamline alignment applications, though it has typically been implemented for particular beamlines and optimization tasks. In this paper, we present a basic formulation of Bayesian inference and Gaussian process models as they relate to multi-objective Bayesian optimization, as well as the practical challenges presented by beamline alignment. We show that the same general implementation of Bayesian optimization with special consideration for beamline alignment can quickly learn the dynamics of particular beamlines in an online fashion through hyperparameter fitting with no prior information. We present the implementation of a concise software framework for beamline alignment and test it on four different optimization problems for experiments on X-ray beamlines at the National Synchrotron Light Source II and the Advanced Light Source, and an electron beam at the Accelerator Test Facility, along with benchmarking on a simulated digital twin. We discuss new applications of the framework, and the potential for a unified approach to beamline alignment at synchrotron facilities.

Prediction of municipal waste generation using multi-expression programming for circular economy: a data-driven approach.

The existing surge in municipal waste generation (MWG), characterized by swiftly changing and uncontrollable factors, poses a significant challenge to sustainable development. This prompted the need for improved predictive models to guide strategic waste management within the circular economy framework. This study aims to develop a predictive model using multi-expression programming (MEP) to assess MWG. The model was developed using historical data on socioeconomic and environmental factors and validated via comparative analyses with artificial neural network (ANN), random forest (RF), and multiple linear regression (MLR) using various evaluation metrics. The parametric and sensitivity analyses of the MEP model were also conducted. The MEP, ANN, RF, and MLR models have a coefficient of determination (R2) (for testing datasets) of 0.977, 0.974, 0.957, and 0.964, respectively. The MEP model is superior in terms of accuracy and performance for the prediction of MWG when compared to the other three models. The sensitivity analysis revealed the relative importance of each input variable in the established MEP model. The novelty of this research lies in the application of MEP to predict MWG and the formulation of a new mathematical model that links socioeconomic and environmental factors with MWG. The model can be used by waste management authorities to optimize waste collection, transportation, and disposal infrastructure for an effective circular economy and sustainable development. This model also aids in the development of effective waste management policies.

Keys to managing university reputation from the students’ perspective

University reputation is a decisive factor in the management, positioning, sustainability, competitiveness, differentiation, and success of universities. However, the measurement of university performance is often communicated through international rankings, which are frequently criticized for not considering the student's perception, who is the primary user of the educational service. For this reason, the objective is to analyze how students' experiences and their perceived value of the educational process influence the final reputation of universities in two different contexts: Colombia and Spain. Additionally, the results of these relationships are contrasted with the cultural differences and educational systems of both countries. The methodology used is quantitative by means of the formulation and demonstration of a structural equation model, with 385 surveys collected from undergraduate students in Colombia and 333 from undergraduate students in Spain. The results confirmed that student experience influences both perceived value and reputation, and perceived value influences the reputation of the university, likewise, the student experience has an indirect effect on reputation through perceived value, with consistent findings in both countries.

Multivariate Cluster Point Process to Quantify and Explore Multi-Entity Configurations: Application to Biofilm Image Data.

Clusters of similar or dissimilar objects are encountered in many fields. Frequently used approaches treat each cluster's central object as latent. Yet, often objects of one or more types cluster around objects of another type. Such arrangements are common in biomedical images of cells, in which nearby cell types likely interact. Quantifying spatial relationships may elucidate biological mechanisms. Parent-offspring statistical frameworks can be usefully applied even when central objects ("parents") differ from peripheral ones ("offspring"). We propose the novel multivariate cluster point process (MCPP) to quantify multi-object (e.g., multi-cellular) arrangements. Unlike commonly used approaches, the MCPP exploits locations of the central parent object in clusters. It accounts for possibly multilayered, multivariate clustering. The model formulation requires specification of which object types function as cluster centers and which reside peripherally. If such information is unknown, the relative roles of object types may be explored by comparing fit of different models via the deviance information criterion (DIC). In simulated data, we compared a series of models' DIC; the MCPP correctly identified simulated relationships. It also produced more accurate and precise parameter estimates than the classical univariate Neyman-Scott process model. We also used the MCPP to quantify proposed configurations and explore new ones in human dental plaque biofilm image data. MCPP models quantified simultaneous clustering of Streptococcus and Porphyromonas around Corynebacterium and of Pasteurellaceae around Streptococcus and successfully captured hypothesized structures for all taxa. Further exploration suggested the presence of clustering between Fusobacterium and Leptotrichia, a previously unreported relationship.