Symmetry structures in dynamic models of biochemical systems

Mapping Intimacies ◽

10.1101/2020.01.27.922005 ◽

2020 ◽

Author(s):

Fredrik Ohlsson ◽

Johannes Borgqvist ◽

Marija Cvijovic

Keyword(s):

Model Selection ◽

Dynamic Models ◽

Model Building ◽

Enzymatic Reaction ◽

Superior Performance ◽

Hill Model ◽

Biochemical Systems ◽

Symmetry Transformations ◽

Model Selection Problem

AbstractSymmetries provide a powerful concept for the development of mechanistic models by describing structures corresponding to the underlying dynamics of biological systems. In this paper, we consider symmetries of the non-linear Hill model describing enzymatic reaction kinetics, and derive a class of symmetry transformations for each order n of the model. We consider a minimal example consisting in the application of symmetry based methods to a model selection problem, where we are able to demonstrate superior performance compared to ordinary residual-based model selection. Finally, we discuss the role of symmetries in systematic model building in systems biology.

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Symmetry structures in dynamic models of biochemical systems

Journal of The Royal Society Interface ◽

10.1098/rsif.2020.0204 ◽

2020 ◽

Vol 17 (168) ◽

pp. 20200204

Author(s):

Fredrik Ohlsson ◽

Johannes Borgqvist ◽

Marija Cvijovic

Keyword(s):

Time Series ◽

Model Selection ◽

Dynamic Models ◽

Model Building ◽

Enzymatic Reaction ◽

Superior Performance ◽

Multiple Time ◽

Hill Model ◽

Complex Interactions ◽

Biochemical Systems

Understanding the complex interactions of biochemical processes underlying human disease represents the holy grail of systems biology. When processes are modelled in ordinary differential equation (ODE) fashion, the most common tool for their analysis is linear stability analysis where the long-term behaviour of the model is determined by linearizing the system around its steady states. However, this asymptotic behaviour is often insufficient for completely determining the structure of the underlying system. A complementary technique for analysing a system of ODEs is to consider the set of symmetries of its solutions. Symmetries provide a powerful concept for the development of mechanistic models by describing structures corresponding to the underlying dynamics of biological systems. To demonstrate their capability, we consider symmetries of the nonlinear Hill model describing enzymatic reaction kinetics and derive a class of symmetry transformations for each order of the model. We consider a minimal example consisting of the application of symmetry-based methods to a model selection problem, where we are able to demonstrate superior performance compared to ordinary residual-based model selection. Moreover, we demonstrate that symmetries reveal the intrinsic properties of a system of interest based on a single time series. Finally, we show and propose that symmetry-based methodology should be considered as the first step in a systematic model building and in the case when multiple time series are available it should complement the commonly used statistical methodologies.

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Machine learning and structural econometrics: contrasts and synergies

Econometrics Journal ◽

10.1093/ectj/utaa019 ◽

2020 ◽

Vol 23 (3) ◽

pp. S81-S124

Author(s):

Fedor Iskhakov ◽

John Rust ◽

Bertel Schjerning

Keyword(s):

Machine Learning ◽

Dynamic Models ◽

Model Building ◽

Empirical Work ◽

Special Issue ◽

Structural Dynamic ◽

Structural Econometrics ◽

Human Creativity ◽

The University

Summary We contrast machine learning (ML) and structural econometrics (SE), focusing on areas where ML can advance the goals of SE. Our views have been informed and inspired by the contributions to this special issue and by papers presented at the second conference on dynamic structural econometrics at the University of Copenhagen in 2018, ‘Methodology and Applications of Structural Dynamic Models and Machine Learning'. ML offers a promising class of techniques that can significantly extend the set of questions we can analyse in SE. The scope, relevance and impact of empirical work in SE can be improved by following the lead of ML in questioning and relaxing the assumption of unbounded rationality. For the foreseeable future, however, ML is unlikely to replace the essential role of human creativity and knowledge in model building and inference, particularly with respect to the key goal of SE, counterfactual prediction.

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Online Reviews and Product Sales: The Role of Review Visibility

Journal of theoretical and applied electronic commerce research ◽

10.3390/jtaer16040038 ◽

2021 ◽

Vol 16 (4) ◽

pp. 638-669

Author(s):

Miriam Alzate ◽

Marta Arce-Urriza ◽

Javier Cebollada

Keyword(s):

Decision Making ◽

Dynamic Models ◽

Generalized Method Of Moments ◽

Online Reviews ◽

Consumer Decision Making ◽

Product Sales ◽

The Impact ◽

The Relationship ◽

The Empirical Analysis

When studying the impact of online reviews on product sales, previous scholars have usually assumed that every review for a product has the same probability of being viewed by consumers. However, decision-making and information processing theories underline that the accessibility of information plays a role in consumer decision-making. We incorporate the notion of review visibility to study the relationship between online reviews and product sales, which is proxied by sales rank information, studying three different cases: (1) when every online review is assumed to have the same probability of being viewed; (2) when we assume that consumers sort online reviews by the most helpful mechanism; and (3) when we assume that consumers sort online reviews by the most recent mechanism. Review non-textual and textual variables are analyzed. The empirical analysis is conducted using a panel of 119 cosmetic products over a period of nine weeks. Using the system generalized method of moments (system GMM) method for dynamic models of panel data, our findings reveal that review variables influence product sales, but the magnitude, and even the direction of the effect, vary amongst visibility cases. Overall, the characteristics of the most helpful reviews have a higher impact on sales.

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Utilization of Eco-Friendly Waste Generated Nanomaterials in Water-Based Drilling Fluids; State of the Art Review

Materials ◽

10.3390/ma14154171 ◽

2021 ◽

Vol 14 (15) ◽

pp. 4171

Author(s):

Rabia Ikram ◽

Badrul Mohamed Jan ◽

Akhmal Sidek ◽

George Kenanakis

Keyword(s):

State Of The Art ◽

Superior Performance ◽

Future Research ◽

Drilling Fluids ◽

Drill Cuttings ◽

Environmental Friendly ◽

Water Based ◽

Drilling Operations ◽

Filtration Properties

An important aspect of hydrocarbon drilling is the usage of drilling fluids, which remove drill cuttings and stabilize the wellbore to provide better filtration. To stabilize these properties, several additives are used in drilling fluids that provide satisfactory rheological and filtration properties. However, commonly used additives are environmentally hazardous; when drilling fluids are disposed after drilling operations, they are discarded with the drill cuttings and additives into water sources and causes unwanted pollution. Therefore, these additives should be substituted with additives that are environmental friendly and provide superior performance. In this regard, biodegradable additives are required for future research. This review investigates the role of various bio-wastes as potential additives to be used in water-based drilling fluids. Furthermore, utilization of these waste-derived nanomaterials is summarized for rheology and lubricity tests. Finally, sufficient rheological and filtration examinations were carried out on water-based drilling fluids to evaluate the effect of wastes as additives on the performance of drilling fluids.

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Social Ontology and Model-Building: A Response to Epstein

Philosophy of the Social Sciences ◽

10.1177/0048393121991728 ◽

2021 ◽

Vol 51 (2) ◽

pp. 176-192

Author(s):

Nadia Ruiz

Keyword(s):

Social Sciences ◽

Social Science ◽

Model Building ◽

Social Ontology ◽

Model Construction ◽

Ontological Commitments ◽

Starting Point ◽

The Social

Brian Epstein has recently argued that a thoroughly microfoundationalist approach towards economics is unconvincing for metaphysical reasons. Generally, Epstein argues that for an improvement in the methodology of social science we must adopt social ontology as the foundation of social sciences; that is, the standing microfoundationalist debate could be solved by fixing economics’ ontology. However, as I show in this paper, fixing the social ontology prior to the process of model construction is optional instead of necessary and that metaphysical-ontological commitments are often the outcome of model construction, not its starting point. By focusing on the practice of modeling in economics the paper provides a useful inroad into the debate about the role of metaphysics in the natural and social sciences more generally.

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Decline in body condition in the Antarctic minke whale (Balaenoptera bonaerensis) in the Southern Ocean during the 1990s

Polar Biology ◽

10.1007/s00300-020-02783-3 ◽

2021 ◽

Vol 44 (2) ◽

pp. 259-273

Author(s):

Céline Cunen ◽

Lars Walløe ◽

Kenji Konishi ◽

Nils Lid Hjort

Keyword(s):

Model Selection ◽

Body Condition ◽

Model Building ◽

Research Question ◽

Information Criterion ◽

The Body ◽

Antarctic Minke Whale ◽

Minke Whales ◽

Balaenoptera Bonaerensis ◽

The Antarctic

AbstractChanges in the body condition of Antarctic minke whales (Balaenoptera bonaerensis) have been investigated in a number of studies, but remain contested. Here we provide a new analysis of body condition measurements, with particularly careful attention to the statistical model building and to model selection issues. We analyse body condition data for a large number (4704) of minke whales caught between 1987 and 2005. The data consist of five different variables related to body condition (fat weight, blubber thickness and girth) and a number of temporal, spatial and biological covariates. The body condition variables are analysed using linear mixed-effects models, for which we provide sound biological motivation. Further, we conduct model selection with the focused information criterion (FIC), reflecting the fact that we have a clearly specified research question, which leads us to a clear focus parameter of particular interest. We find that there has been a substantial decline in body condition over the study period (the net declines are estimated to 10% for fat weight, 7% for blubber thickness and 3% for the girth). Interestingly, there seems to be some differences in body condition trends between males and females and in different regions of the Antarctic. The decline in body condition could indicate major changes in the Antarctic ecosystem, in particular, increased competition from some larger krill-eating whale species.

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Assessing the Unacquainted: Inferred Reviewer Personality and Review Helpfulness

MIS Quarterly ◽

10.25300/misq/2021/14375 ◽

2021 ◽

Vol 45 (3) ◽

pp. 1113-1148

Author(s):

Angela Xia Liu ◽

◽

Yilin Li ◽

Sean Xu ◽

◽

...

Keyword(s):

Personality Traits ◽

Supervised Classification ◽

Large Population ◽

Superior Performance ◽

Product Reviews ◽

Review Helpfulness ◽

Personality Theories ◽

Deep Learning Model ◽

Practical Implications

This work examines the question of who is more likely to provide future helpful reviews in the context of online product reviews by synergistically using personality theories and data analytics. It trains a deep learning model to infer a reviewer’s personality traits. This enables analyses to reveal the role of personality traits in review helpfulness among a large population of reviewers. We develop hypotheses on how personality traits are associated with review helpfulness, followed by hypotheses testing that confirms that higher review helpfulness is related to higher openness, conscientiousness, extraversion, and agreeableness and to lower emotional stability. These results suggest the appropriateness of using these five personality traits as inputs for developing a model for predicting future review helpfulness. Based on an ensemble model using supervised classification algorithms, we develop a predictive model and demonstrate its superior performance. Theoretical and practical implications are discussed.

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Impact of organizational citizenship behavior on job performance in Indian healthcare industries

International Journal of Productivity and Performance Management ◽

10.1108/ijppm-02-2016-0048 ◽

2017 ◽

Vol 66 (6) ◽

pp. 780-796 ◽

Cited By ~ 16

Author(s):

Eeman Basu ◽

Rabindra Kumar Pradhan ◽

Hare Ram Tewari

Keyword(s):

Social Capital ◽

Job Performance ◽

Organizational Citizenship ◽

Organizational Citizenship Behavior ◽

Superior Performance ◽

Citizenship Behavior ◽

Healthcare Organizations ◽

Content Type ◽

The Relationship

Purpose The purpose of this paper is to explore the relationship between organizational citizenship behavior (OCB) and job performance. It also examines the mediating role of social capital in influencing the relationship between OCB and job performance. Design/methodology/approach The study explores the dynamic relationship among the variables of OCB and job performance and social capital. Data were collected from 501 respondents working in 15 healthcare organizations in Kolkata, India, through questionnaire survey. Likert-type rating scales of OCB, job performance and social capital with sound reliability and validity were used to carry out the survey. The data were analyzed using structural equation modeling. Findings The results of the present study show that OCB significantly predicts job performance in healthcare organizations. Social capital found to be a significant mediator between OCB and job performance. Research limitations/implications The findings of the study have a number of implications for organizations in acknowledging and leveraging social capital and encouraging OCB to facilitate superior performance of employees. The generalization of the findings of the study should be restricted to the healthcare organizations in Kolkata due to its own style of functioning, workforce and work environment. The role of demographic variables in influencing the outcome measures has not been considered for the present study. Further research on these aspects may reveal more interesting results with regard to the dynamics among organizational citizenship behavior, social capital and job performance. Practical implications Employee-friendly management practices should be adopted in organizations to facilitate the formation of network building and development of social capital which serves as an asset to organizations and creates competitive advantage. Originality/value The research findings enrich our understanding of voluntary social participation and citizenship behavior of employees for influencing performance at work. The study also provides useful and unique insight on the benefits of networking in healthcare organizations particularly helping employees to cope with emergency situations. The findings as well as methodology used in this study are original and unique.

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