Cancer is a complex disease, necessitating research on many different levels; at the subcellular level to identify genes, proteins and signaling pathways associated with the disease; at the cellular level to identify, for example, cell-cell adhesion and communication mechanisms; at the tissue level to investigate disruption of homeostasis and interaction with the tissue of origin or settlement of metastasis; and finally at the systems level to explore its global impact, e.g. through the mechanism of cachexia. Mathematical models have been proposed (...) to identify key mechanisms that underlie dynamics and events at every scale of interest, and increasing effort is now being paid to multi-scale models that bridge the different scales. With more biological data becoming available and with increased interdisciplinary efforts, theoretical models are rendering suitable tools to predict the origin and course of the disease. The ultimate aims of cancer models, however, are to enlighten our concept of the carcinogenesis process and to assist in the designing of treatment protocols that can reduce mortality and improve patient quality of life. Conventional treatment of cancer is surgery combined with radiotherapy or chemotherapy for localized tumors or systemic treatment of advanced cancers, respectively. Although radiation is widely used as treatment, most scheduling is based on empirical knowledge and less on the predictions of sophisticated growth dynamical models of treatment response. Part of the failure to translate modeling research to the clinic may stem from language barriers, exacerbated by often esoteric model renderings with inaccessible parameterization. Here we discuss some ideas for combining tractable dynamical tumor growth models with radiation response models using biologically accessible parameters to provide a more intuitive and exploitable framework for understanding the complexity of radiotherapy treatment and failure. (shrink)

In this paper, we provide a re-interpretation of qualitative and quantitative modeling from a representationalist perspective. In this view, both approaches attempt to construct abstract representations of empirical relational structures. Whereas quantitative research uses variable-based models that abstract from individual cases, qualitative research favors case-based models that abstract from individual characteristics. Variable-based models are usually stated in the form of quantified sentences. This syntactic structure implies that sentences about individual cases are derived using deductive reasoning. In contrast, (...) case-based models are usually stated using context-dependent existential sentences. This syntactic structure implies that sentences about other cases are justifiable by inductive reasoning. We apply this representationalist perspective to the problems of generalization and replication. Using the analytical framework of modal logic, we argue that the modes of reasoning are often not only applied to the context that has been studied empirically, but also on a between-contexts level. Consequently, quantitative researchers mostly adhere to a top-down strategy of generalization, whereas qualitative researchers usually follow a bottom-up strategy of generalization. Depending on which strategy is employed, the role of replication attempts is very different. In deductive reasoning, replication attempts serve as empirical tests of the underlying theory. Therefore, failed replications imply a faulty theory. From an inductive perspective, however, replication attempts serve to explore the scope of the theory. Consequently, failed replications do not question the theory per se, but help to shape its boundary conditions. We conclude that quantitative research may benefit from a bottom-up generalization strategy as it is employed in most qualitative research programs. Inductive reasoning forces us to think about the boundary conditions of our theories and provides a framework for generalization beyond statistical testing. In this perspective, failed replications are just as informative as successful replications, because they help to explore the scope of our theories. (shrink)

Conscious experiences are characterized by mental qualities, such as those involved in seeing red, feeling pain, or smelling cinnamon. The standard framework for modeling mental qualities represents them via points in geometrical spaces, where distances between points inversely correspond to degrees of phenomenal similarity. This paper argues that the standard framework is structurally inadequate and develops a new framework that is more powerful and flexible. The core problem for the standard framework is that it cannot capture precision structure: for (...) example, consider the phenomenal contrast between seeing an object as crimson in foveal vision versus merely as red in peripheral vision. The solution I favor is to model mental qualities using regions, rather than points. I explain how this seemingly simple formal innovation not only provides a natural way of modeling precision, but also yields a variety of further theoretical fruits: it enables us to formulate novel hypotheses about the space and structures of mental qualities, formally differentiate two dimensions of phenomenal similarity, generate a quantitative model of the phenomenal sorites, and define a measure of discriminatory grain. A noteworthy consequence is that the structure of the mental qualities of conscious experiences is fundamentally different from the structure of the perceptible qualities of external objects. (shrink)

This essay provides an introduction to the terminology, concepts, methods, and challenges of image‐based modeling in biology. Image‐based modeling and simulation aims at using systematic, quantitative image data to build predictive models of biological systems that can be simulated with a computer. This allows one to disentangle molecular mechanisms from effects of shape and geometry. Questions like “what is the functional role of shape” or “how are biological shapes generated and regulated” can be addressed in the framework (...) of image‐based systems biology. The combination of image quantification, model building, and computer simulation is illustrated here using the example of diffusion in the endoplasmic reticulum. (shrink)

The appeal to expert opinion is an argument form that uses the verdict of an expert to support a position or hypothesis. A previous scheme-based treatment of the argument form is formalized within a Bayesian network that is able to capture the critical aspects of the argument form, including the central considerations of the expert's expertise and trustworthiness. We propose this as an appropriate normative framework for the argument form, enabling the development and testing of quantitative predictions as to (...) how people evaluate this argument, suggesting that such an approach might be beneficial to argumentation research generally. We subsequently present two experiments as an example of the potential for future research in this vein, demonstrating that participants' quantitative ratings of the convincingness of a proposition that has been supported with an appeal to expert opinion were broadly consistent with the predictions of the Bayesian model. (shrink)

Quantitative analysts or “Quants” are a source of competitive advantage for financial institutions. They occupy the relatively powerful but often misunderstood role of modeling, structuring, and pricing complex financial instruments in the capital markets. But Quants often function in a discipline free from ethical burdens. Models used to price complex instruments are usually beyond the mathematical understanding of financial sector participants who rely heavily on the integrity of the Quant who built them. Although there has been some attempt (...) to cover the ethics of mathematics applied to the capital markets, designing a set of rules to guide the ethical behavior of Quants cannot be made explicit and remains inexpressible. Because Quants generally experience a sense of detachment from moral obligation, there is a growing need to convert moral detachment into engagement. Our framework is indebted to key elements of Wittgenstein’s practical ethics philosophy and Rawls’ justice principle. The burden of balancing justice as fairness as defined by Rawls with the inability to explicitly articulate ethical rules as defined by Wittgenstein must fall to the Quant. We propose that the threshold delineating the barrier between ethical detachment and engagement can only be defined by the Quants themselves. It is their moral duty to disclose their level of ethical engagement when their models are put into practice. (shrink)

Probabilistic models of sentence comprehension are increasingly relevant to questions concerning human language processing. However, such models are often limited to syntactic factors. This restriction is unrealistic in light of experimental results suggesting interactions between syntax and other forms of linguistic information in human sentence processing. To address this limitation, this article introduces two sentence processing models that augment a syntactic component with information about discourse co-reference. The novel combination of probabilistic syntactic components with co-reference classifiers permits them to more (...) closely mimic human behavior than existing models. The first model uses a deep model of linguistics, based in part on probabilistic logic, allowing it to make qualitative predictions on experimental data; the second model uses shallow processing to make quantitative predictions on a broad-coverage reading-time corpus. (shrink)

Journal of the History of Biology provides a fifty-year long record for examining the evolution of the history of biology as a scholarly discipline. In this paper, we present a new dataset and preliminary quantitative analysis of the thematic content of JHB from the perspectives of geography, organisms, and thematic fields. The geographic diversity of authors whose work appears in JHB has increased steadily since 1968, but the geographic coverage of the content of JHB articles remains strongly lopsided toward (...) the United States, United Kingdom, and western Europe and has diversified much less dramatically over time. The taxonomic diversity of organisms discussed in JHB increased steadily between 1968 and the late 1990s but declined in later years, mirroring broader patterns of diversification previously reported in the biomedical research literature. Finally, we used a combination of topic modeling and nonlinear dimensionality reduction techniques to develop a model of multi-article fields within JHB. We found evidence for directional changes in the representation of fields on multiple scales. The diversity of JHB with regard to the representation of thematic fields has increased overall, with most of that diversification occurring in recent years. Drawing on the dataset generated in the course of this analysis, as well as web services in the emerging digital history and philosophy of science ecosystem, we have developed an interactive web platform for exploring the content of JHB, and we provide a brief overview of the platform in this article. As a whole, the data and analyses presented here provide a starting-place for further critical reflection on the evolution of the history of biology over the past half-century. (shrink)

In this study, we apply MOSAIC (model of syntax acquisition in children) to the simulation of the developmental patterning of children's optional infinitive (OI) errors in 4 languages: English, Dutch, German, and Spanish. MOSAIC, which has already simulated this phenomenon in Dutch and English, now implements a learning mechanism that better reflects the theoretical assumptions underlying it, as well as a chunking mechanism that results in frequent phrases being treated as 1 unit. Using 1, identical model that learns from child‐directed (...) speech, we obtain a close quantitative fit to the data from all 4 languages despite there being considerable cross‐linguistic and developmental variation in the OI phenomenon. MOSAIC successfully simulates the difference between Spanish (a pro‐drop language in which OI errors are virtually absent) and obligatory subject languages that do display the OI phenomenon. It also highlights differences in the OI phenomenon across German and Dutch, 2 closely related languages whose grammar is virtually identical with respect to the relation between finiteness and verb placement. Taken together, these results suggest that (a) cross‐linguistic differences in the rates at which children produce OIs are graded, quantitative differences that closely reflect the statistical properties of the input they are exposed to and (b) theories of syntax acquisition need to consider more closely the role of input characteristics as determinants of quantitative differences in the cross‐linguistic patterning of phenomena in language acquisition. (shrink)

In recent years, the emergence of a new trend in contemporary philosophy has been observed in the increasing usage of empirical research methods to conduct philosophical inquiries. Although philosophers primarily use secondary data from other disciplines or apply quantitative methods (experiments, surveys, etc.), the rise of qualitative methods (e.g., in-depth interviews, participant observations and qualitative text analysis) can also be observed. In this paper, I focus on how qualitative research methods can be applied within philosophy of science, namely within (...) the philosophical debate on modeling. Specifically, I review my empirical investigations into the issues of model de-idealization, model justification and performativity. (shrink)

The Representational Theory of Measurement conceives measurement as establishing homomorphisms from empirical relational structures into numerical relation structures, called models. There are two different approaches to deal with the justification of a model: an axiomatic and an empirical approach. The axiomatic approach verifies whether a given relational structure satisfies certain axioms to secure homomorphic mapping. The empirical approach conceives models to function as measuring instruments by transferring observations of a phenomenon under investigation into quantitative facts about that phenomenon. These (...) facts are evaluated by their accuracy and precision. Precision is generally achieved by least squares methods and accuracy by calibration. For calibration standards are needed. Then two polar strategies can be distinguished: white-box modeling and black-box modeling. The first strategy of modeling aims at estimating the invariant equations of the phenomenon, thereby fulfilling Hertz’s correctness requirement. The latter strategy of modeling is to use known stable facts about the phenomenon to adjust the model parameters, thereby fulfilling Hertz’s appropriateness requirement. For this latter strategy, the requirement of models as homomorphic mappings has been dropped. Where one will find the axiomatic approach more often used for measurement in the laboratory, the empirical approach is more appropriate for measurement outside the laboratory. The reason for this is that for measurement of phenomena outside the laboratory, one also needs to take account of the environment to achieve accurate results. Environments are generally too relation-rich for an axiomatic approach, which are only applicable for relation-poor systems. The white-box modeling strategy, reflecting the complexity of the environment due to its correctness requirement, will, however, lead to immensely large models. To avoid this problem, modular design is an appropriate strategy to reduce this complexity. Modular design is a grey-box modeling strategy. Grey-box models are assemblies of modules; these are black boxes with standard interface. It should be noted that the structure of the assemblage need not be homomorphic to the relations describing the interaction between phenomenon and environment. These three modeling strategies map out the possible designs for computer simulations as measuring instruments. Whether a simulation is based on a white-box, grey-box or black-box model is only determined by the relationship between the phenomenon and its environment and not by e.g. its materiality or physicality. (shrink)

Confronted with the possibility of severe environmental harms, such as catastrophic climate change, some researchers have suggested that we should abandon the principle at the heart of standard decision theory—the injunction to maximize expected utility—and embrace a different one: the Precautionary Principle. Arguably, the most sophisticated philosophical treatment of the Precautionary Principle is due to Steel. Steel interprets PP as a qualitative decision rule and appears to conclude that a quantitative decision-theoretic statement of PP is both impossible and unnecessary. (...) In this article, we propose a decision-theoretic formulation of PP in terms of lexical utilities. We show that this lexical model is largely faithful to Steel’s approach, but also that it corrects three problems with Steel’s account and clarifies the relationship between PP and standard decision theory. Using a range of examples, we illustrate how the lexical model can be used to explore a variety of issues related to precautionary reasoning. (shrink)

This article reports the results of research to develop a survey instrument and its use to validate an ethical business culture construct (CEBC Model). The reported three-stage quantitative study builds on our previous qualitative work, aimed at identifying dimensions of ethical business cultures. The research resulted in a parsimonious construct, covering five dimensions of ethical business cultures, and a ten-question instrument, measuring this construct. In this article, we report results of exploratory and confirmatory factor analyses and convergent construct validity (...) testing, discuss the potential applications of the construct and instrument in assessment and development of ethical business cultures, and provide recommendations for industry practitioners and for further research. (shrink)

This article presents a quantitative way of modeling the interim decisions of clinical trials. While statistical approaches tend to focus on the epistemic aspects of statistical monitoring rules, often overlooking ethical considerations, ethical approaches tend to neglect key epistemic dimension. The proposal is a second-order decision theoretic framework. The framework provides means for retrospective assessment of interim decisions based on a clear and consistent set of criteria that combines both ethical and epistemic considerations. The framework is broadly Bayesian (...) and addresses a fundamental question behind many concerns about clinical trials: What does it take for an interim decision (e.g., whether to stop the trial, or continue) to be a good decision? I provide simulation illustrating the modeling of interim decisions counterfactually using the framework. (shrink)

How do adolescent girls envision the world of work and their potential place in it? This article considers teen magazines as a possible source for girls’ perceptions about the work world, including their own career futures. The author explores the occupational landscape embedded with in Seventeen magazinein 1992 in both quantitative and qualitative terms. The labor market in Seventeen-land is heavily skewed toward professional occupations, particularly in the entertainment industry. A close reading of the text reveals four primary messages (...) about the world of work: Entertainment careers are a viable and prestigious option, men are the norm as workers, men hold the power, and fashion modeling is the pinnacle of “women’s work. ” The author argues that Seventeen may be promulgating a distinct set of what Collins called “controlling images” directed at predominantly white girls. The findings suggest gender researchers should attend to the connection between the mass media and girl culture. They also underscore the importance of teaching media literacy. (shrink)

Individuals make decisions under uncertainty every day. Decisions are based on in- complete information concerning the potential outcome or the predicted likelihood with which events occur. In addition, individuals’ choices often deviate from the rational or mathematically objective solution. Accordingly, the dynamics of human decision making are difficult to capture using conventional, linear mathematical models. Here, we present data from a 2-choice task with variable risk between sure loss and risky loss to illustrate how a simple nonlinear dynamical system can (...) be employed to capture the dynamics of human decision making under uncertainty (i.e., multistability, bifurcations). We test the feasibility of this model quantitatively and demonstrate how the model can account for up to 86% of the observed choice behavior. The implications of using dynamical models for explaining the nonlin- ear complexities of human decision making are discussed as well as the degree to which the theory of nonlinear dynamical systems might offer an alternative framework for understanding human decision making processes. (shrink)

Computer aided modeling and simulation of nanomaterials can describe the correlation between the material’s microstructure and its macroscopic properties quantitatively. In this paper, we propose an integrated modeling, simulation, and visualization approach for designing nanomaterials. Firstly, a fast parametric modeling method for important nanomaterials such as graphene, nanotubes, and MOFs is proposed; secondly, the material model could be edited adaptively without affecting the validity of the model on the physical level; thirdly a preliminary calculation for nanomaterials’ energy (...) is implemented based on the theory of surface fitting; finally, an integrated framework of nanomaterials modeling, simulation, and visualization is designed and implemented. Experimental results show that the proposed approach is feasible and effective. (shrink)

Mechanisms play an important role in many sciences when it comes to questions concerning explanation, prediction, and control. Answering such questions in a quantitative way requires a formal represention of mechanisms. Gebharter (2014) suggests to represent mechanisms by means of one or more causal arrows of an acyclic causal net. In this paper we show how this approach can be extended in such a way that it can also be fruitfully applied to mechanisms featuring causal feedback.

One recent priority of the U.S. government is developing autonomous robotic systems. The U.S. Army has funded research to design a metric of evil to support military commanders with ethical decision-making and, in the future, allow robotic military systems to make autonomous ethical judgments. We use this particular project as a case study for efforts that seek to frame morality in quantitative terms. We report preliminary results from this research, describing the assumptions and limitations of a program that assesses (...) the relative evil of two courses of action. We compare this program to other attempts to simulate ethical decision-making, assess possibilities for overcoming the trade-off between input simplification and output reliability, and discuss the responsibilities of users and designers in implementing such programs. We conclude by discussing the implications that this project highlights for the successes and challenges of developing automated mechanisms for ethical decision making. (shrink)

In this paper I argue that the appropriate analogy for “understanding what makes simulation results reliable” in global climate modeling is not with scientific experimentation or measurement, but—at least in the case of the use of global climate models for policy development—with the applications of science in applied design problems. The prospects for using this analogy to argue for the quantitative reliability of GCMs are assessed and compared with other potential strategies.

In late 2019, the COVID-19 pandemic began to spread over the world, causing millions of deaths. In the first few months of the pandemic, several countries prevented the spread of the pandemic successfully. By contrast, the pandemic in many other countries was not controlled well. For example, India encountered a second serious outbreak of COVID-19 from April 2021 due to the poor resistance measures implemented by the government. To figure out the effective countermeasures to the pandemic, this research proposes a (...) COVID-19 pandemic and its response system, which consists of the infection subsystem, the quarantine subsystem, and the medical subsystem. On this basis, an improved SEIR-SD model is established which is utilized to analyze the response measures to the pandemic quantitatively. This model successfully simulates the actual epidemic scenarios in Wuhan, which verifies its effectiveness. Afterward, the impact of hospital administration rate, quarantine rate, average contact number, and contact infection rate on the cumulative number of infections and deaths are analyzed by simulation. The results show that both the medical and administrative efforts, especially in the early stage of the epidemic, are significant in reducing the number of infections and shortening the epidemic period. In the medical aspect, the more stringent quarantine brings the earlier inflection point of the epidemic; more importantly, improving the treatment rate significantly reduces the scale of the epidemic. In the administrative aspect, enforcing individual protection and strict community closure can effectively cut off the transmission of the virus and curb the spread of the epidemic. Finally, this research proposes several practical suggestions in response to the COVID-19 pandemic. The main contribution of this research is that the effects of different response measures on the number of new infections daily and the cumulative number of deaths of a country or region in the COVID-19 pandemic are estimated quantitatively based on modeling and simulation. (shrink)

BackgroundReflexive pitch perturbation experiments are commonly used to investigate the neural mechanisms underlying vocal motor control. In these experiments, the fundamental frequency–the acoustic correlate of pitch–of a speech signal is shifted unexpectedly and played back to the speaker via headphones in near real-time. In response to the shift, speakers increase or decrease their fundamental frequency in the direction opposing the shift so that their perceived pitch is closer to what they intended. The goal of the current work is to develop (...) a quantitative model of responses to reflexive perturbations that can be interpreted in terms of the physiological mechanisms underlying the response and that captures both group-mean data and individual subject responses.MethodsA model framework was established that allowed the specification of several models based on Proportional-Integral-Derivative and State-Space/Directions Into Velocities of Articulators (DIVA) model classes. The performance of 19 models was compared in fitting experimental data from two published studies. The models were evaluated in terms of their ability to capture both population-level responses and individual differences in sensorimotor control processes.ResultsA three-parameter DIVA model performed best when fitting group-mean data from both studies; this model is equivalent to a single-rate state-space model and a first-order low pass filter model. The same model also provided stable estimates of parameters across samples from individual subject data and performed among the best models to differentiate between subjects. The three parameters correspond to gains in the auditory feedback controller’s response to a perceived error, the delay of this response, and the gain of the somatosensory feedback controller’s “resistance” to this correction. Excellent fits were also obtained from a four-parameter model with an additional auditory velocity error term; this model was better able to capture multi-component reflexive responses seen in some individual subjects.ConclusionOur results demonstrate the stereotyped nature of an individual’s responses to pitch perturbations. Further, we identified a model that captures population responses to pitch perturbations and characterizes individual differences in a stable manner with parameters that relate to underlying motor control capabilities. Future work will evaluate the model in characterizing responses from individuals with communication disorders. (shrink)

In the present study, we have demonstrated hysteresis phenomena in the excitability of single, enzymatically dissociated guinea pig ventricular myocytes. Membrane potentials were recorded with patch pipettes in the whole-cell current clamp configuration. Repetitive stimulation with depolarizing current pulses of constant cycle length and duration but varying strength led to predictable excitation (1:l) and non-excitation (1:0) patterns depending on current strength. In addition, transition between patterns depended on the direction of current intensity change and stable hysteresis loops were obtained in (...) stimulus:response pattern vs. current intensity plots in 14 cells. Increase of pulse duration and decrease of stimulation rate contributed to a reduction in hysteresis loop areas. Changes in amplitude and shape of the subthreshold responses during the transitions from one stable pattern to the other, suggested that activity led to an increase in membrane resistance, particularly in the voltage domain between resting potential, and threshold. Therefore, we modelled the dynamic behaviour of the single cells as a function of diastolic membrane resistance, using previously published analytical solutions. Numerical iteration of the analytical model equations closely reproduced the experimental hysteresis loops in both qualitative and quantitative ways. In particular, the effect of stimulation frequency on the model was similar to the experimental findings. The overall study suggests that the excitability pattern of guinea pig ventricular myocytes accounts for hysteresis and bistabilities when current intensity is allowed to fluctuate around threshold levels. (shrink)

A predictive model applicable in both neurophysiological and decision-making studies is proposed, bridging the gap between psychological/behavioral and neurophysiological studies. Supposing the electromagnetic waves are carriers of decision-making, and electromagnetic waves with the same frequency, individual amplitude and constant phase triggered by conditions interfere with each other and the resultant intensity determines the probability of the decision. Accordingly, brainwave-interference decision-making model is built mathematically and empirically test with neurophysiological and behavioral data. Event-related potential data confirmed the stability of the phase (...) differences in a given decision context. Behavioral data analysis shows that phase stability exists across categorization-decision, two-stage gambling, and prisoner’s dilemma decisions. Irrational decisions occurring in those experiments are actually rational as their phases could be quantitatively derived from the phases of the riskiest and safest choices. Model fitting result reveals that the root-mean-square deviations between the fitted and actual phases of irrational decisions are less than 10°, and the mean absolute percentage errors of the fitted probabilities are less than 0.06. The proposed model is similar in mathematical form compared with the quantum modeling approach, but endowed with physiological/psychological connection and predictive ability, and promising in the integration of neurophysiological and behavioral research to explore the origin of the decision. (shrink)

In this paper I argue that the appropriate analogy for “understanding what makes simulation results reliable” in Global Climate Modeling is not with scientific experimentation or measurement, but—at least in the case of the use of global climate models for policy development—with the applications of science in engineering design problems. The prospects for using this analogy to argue for the quantitative reliability of GCMs are assessed and compared with other potential strategies.

This paper provides a method for characterizing space events using the framework of conceptual spaces. We focus specifically on estimating and ranking the likelihood of collisions between space objects. The objective is to design an approach for anticipatory decision support for space operators who can take preventive actions on the basis of assessments of relative risk. To make this possible our approach draws on the fusion of both hard and soft data within a single decision support framework. Contextual data is (...) also taken into account, for example data about space weather effects, by drawing on the Space Domain Ontologies, a large system of ontologies designed to support all aspects of space situational awareness. The framework is coupled with a mathematical programming scheme that frames a mathematically optimal approach for decision support, providing a quantitative basis for ranking potential for collision across multiple satellite pairs. The goal is to provide the broadest possible information foundation for critical assessments of collision likelihood. (shrink)

This paper outlines a critique of the use of the genetic variance–covariance matrix (G), one of the central concepts in the modern study of natural selection and evolution. Specifically, I argue that for both conceptual and empirical reasons, studies of G cannot be used to elucidate so-called constraints on natural selection, nor can they be employed to detect or to measure past selection in natural populations – contrary to what assumed by most practicing biologists. I suggest that the search for (...) a general solution to the difficult problem of identifying causal structures given observed correlation’s has led evolutionary quantitative geneticists to substitute statistical modeling for the more difficult, but much more valuable, job of teasing apart the many possible causes underlying the action of natural selection. Hence, the entire evolutionary quantitative genetics research program may be in need of a fundamental reconsideration of its goals and how they correspond to the array of mathematical and experimental techniques normally employed by its practitioners. (shrink)

Richard Levins has advocated the scientific merits of qualitative modeling throughout his career. He believed an excessive and uncritical focus on emulating the models used by physicists and maximizing quantitative precision was hindering biological theorizing in particular. Greater emphasis on qualitative properties of modeled systems would help counteract this tendency, and Levins subsequently developed one method of qualitative modeling, loop analysis, to study a wide variety of biological phenomena. Qualitative modeling has been criticized for being conceptually (...) and methodologically problematic. As a clear example of a qualitative modeling method, loop analysis shows this criticism is indefensible. The method has, however, some serious limitations. This paper describes loop analysis, its limitations, and attempts to clarify the differences between quantitative and qualitative modeling, in content and objective. Loop analysis is but one of numerous types of qualitative analysis, so its limitations do not detract from the currently underappreciated and underdeveloped role qualitative modeling could have within science. (shrink)

Shared conceptualization, in the sense we take it here, is as recent a notion as the Semantic Web, but its relevance for a large variety of fields requires efficient methods of extraction and representation for both quantitative and qualitative data. This notion is particularly relevant for the investigation into, and construction of, semantic structures such as knowledge bases and taxonomies, but given the required large, often inaccurate, corpora available for search we can get only approximations. We see fuzzy description (...) logic as an adequate medium for the representation of human semantic knowledge and propose a means to couple it with fuzzy semantic networks via the propositional Łukasiewicz fuzzy logic such that these suffice for decidability for queries over a semantic-knowledge base such as “to what degree of sharedness does it entail the instantiation C(a) for some concept C” or “what are the roles R that connect the individuals a and b to degree of sharedness ε.” . (shrink)

This paper concerns design thinking (Lawson, 1980), system thinking (systems theory) (von Bertalanffy, 1968), and system dynamics modeling as methodological platforms for analyzing large amounts of qualitative data and transforming it into quantitative mode. The aims of this article are to present an integral (mixed) research process including the design thinking process—a solution oriented approach applicable in the social sciences and humanities which enables to reveal causality in research on societal and behavioral issues. This integral approach is illustrated (...) by an empirical pilot study from art/design-educational environment. (shrink)

Throughout the Covid-19 pandemic, people have been eager to learn what factors, and especially what public health policies, cause infection rates to wax and wane. But figuring out conclusively what causes what is difficult in complex systems with nonlinear dynamics, such as pandemics. We review some of the challenges that scientists have faced in answering quantitative causal questions during the Covid-19 pandemic, and suggest that these challenges are a reason to augment the moral dimension of conversations about causal inference. (...) We take a lesson from Martha Nussbaum—who cautions us not to think we have just one question on our hands when we have at least two—and apply it to modeling for causal inference in the context of cost-benefit analysis. (shrink)

Parametric cognitive models are increasingly popular tools for analyzing data obtained from psychological experiments. One of the main goals of such models is to formalize psychological theories using parameters that represent distinct psychological processes. We argue that systematic quantitative reviews of parameter estimates can make an important contribution to robust and cumulative cognitive modeling. Parameter reviews can benefit model development and model assessment by providing valuable information about the expected parameter space, and can facilitate the more efficient design (...) of experiments. Importantly, parameter reviews provide crucial—if not indispensable—information for the specification of informative prior distributions in Bayesian cognitive modeling. From the Bayesian perspective, prior distributions are an integral part of a model, reflecting cumulative theoretical knowledge about plausible values of the model's parameters (Lee,2018). In this paper we illustrate how systematic parameter reviews can be implemented to generate informed prior distributions for the Diffusion Decision Model (DDM; Ratcliff and McKoon,2008), the most widely used model of speeded decision making. We surveyed the published literature on empirical applications of the DDM, extracted the reported parameter estimates, and synthesized this information in the form of prior distributions. Our parameter review establishes a comprehensive reference resource for plausible DDM parameter values in various experimental paradigms that can guide future applications of the model. Based on the challenges we faced during the parameter review, we formulate a set of general and DDM-specific suggestions aiming to increase reproducibility and the information gained from the review process. (shrink)

Research on economization processes is increasingly taking seriously the social and material processes through which various policy domains are transformed into economic problems and solutions. This article engages “Value Added Modeling” (VAM) in teacher evaluation systems as a case study in economization. VAM is a statistical technology for evaluating the effectiveness of schoolteachers using student test scores, which wrests authority for the determination of quality teaching away from education professionals and toward quantitative economic modelers. Mobilizing field theory, we (...) trace a half century of changing relationships among economists, other academics, and various policy audiences (from media to philanthropists to state and federal government) in struggles to define education policy concerning teacher quality. We show that economization is a set of overlapping, sometimes contradictory processes that can take different forms: in this case, the spread of an “economic style of reasoning” or the establishment of “economic policy devices.” The case of VAM shows stages of economization in which processes first proceeded independently of one another, then interacted in contradictory ways, and finally, mutually reinforced one another. What primarily drove these interactions was the struggle for scientific capital within the economics discipline and the changing place of education policy and VAM within it. Ultimately, VAM’s original role as a policy device for evaluating and selecting individual teachers has foundered even as it has become an important tool for economists to accrue scientific capital and expand their style of reasoning to broader audiences. (shrink)

Mechanist philosophers have examined several strategies scientists use for discovering causal mechanisms in neuroscience. Findings about the anatomical organization of the brain play a central role in several such strategies. Little attention has been paid, however, to the use of network analysis and causal modeling techniques for mechanism discovery. In particular, mechanist philosophers have not explored whether and how these strategies incorporate information about the anatomical organization of the brain. This paper clarifies these issues in the light of the (...) distinction between structural, functional and effective connectivity. Specifically, we examine two quantitative strategies currently used for causal discovery from functional neuroimaging data: dynamic causal modeling and probabilistic graphical modeling. We show that dynamic causal modeling uses findings about the brain’s anatomical organization to improve the statistical estimation of parameters in an already specified causal model of the target brain mechanism. Probabilistic graphical modeling, in contrast, makes no appeal to the brain’s anatomical organization, but lays bare the conditions under which correlational data suffice to license reliable inferences about the causal organization of a target brain mechanism. The question of whether findings about the anatomical organization of the brain can and should constrain the inference of causal networks remains open, but we show how the tools supplied by graphical modeling methods help to address it. (shrink)

In online communities, such as Twitter, Facebook, or Reddit, millions of pieces of contents are generated by users every day, and these user-generated contents show a great variety of topics discussed that make the online community vivid and attractive. However, the reasons why UGCs show great variety and how a firm can influence this variety was unknown, which had been an obstacle to understanding and managing UGCs’ variety. This study fills these two gaps based on variety-seeking theory and topic (...) class='Hi'>modeling, which is a technique in machine learning. We extract, quantitatively, the topic of the UGCs using topic modeling and divide UGCs into two types: single topic and multiple topics. The user’s tendency to choose the type of UGC is used to measure variety-seeking behavior. We found that users have an intrinsic preference for variety when producing UGCs; the more single topic UGCs were produced in the past, the higher the probability of producing multiple topics UGC and the lower the probability of producing single topic UGC would be in the next, and vice versa. Furthermore, we discussed the effect of language/linguistic style matching between firm feedbacks and UGCs on users’ variety-seeking tendencies in UGCs’ production. This study makes three contributions: broadening variety-seeking theory to new behavior, that is content production behavior, and the results demonstrated that people would show a variety-seeking behavior in producing UGCs. a new feasible method to measure the variety of UGCs by using topic modeling to extract the topics of UGCs and then measure the variety-seeking behavior in producing UGCs by analyzing the choice between single topic and multiple topics. guidance for the firm to alter LSM of feedbacks to influence the variety of UGCs. (shrink)

Blumenthal-Barby and her colleagues (2022) situate their discussion of philosophy and bioethics in the context of (reportedly) widely held assumption that, when compared to the early days of bioethics, the role of philosophy is now diminished across the field – the assumption we call the Disconnection Thesis. This assumption can be summarized, to use the authors’ own words, by the phrase “philosophy’s glory days in bioethics are over“. While in no place of the article they explicitly endorse the Disconnection Thesis, (...) at least some of the authors had previously endorsed it in print (Savulescu 2015). Such expressions of collective expert wisdom might be a valuable source of information on the discipline's history, but they should not be accepted uncritically. Given the explosion in the size and scope of bioethical research in recent decades, any scholar’s familiarity with the area is necessarily based on selective reading and might be biased. Hence, in this commentary, we examine what kind of more rigorous evidence could corroborate the Disconnection Thesis. In other words, if the role of philosophy in bioethics has been indeed diminishing, what kind of observable patterns should we expect to see? Drawing on our previous research (Bystranowski, Dranseika, Żuradzki 2022), here we focus on two useful perspectives: citation analysis and topic modeling. While the first approach allows us to indirectly measure the level of engagement of bioethicists with philosophical literature (by measuring the proportion of references from articles published in journals in bioethics that cite philosophy journals), the latter provides a window into the content and argumentative style of bioethical texts. (shrink)

Although predictive power and explanatory insight are both desiderata of scientific models, these features are often in tension with each other and cannot be simultaneously maximized. In such situations, scientists may adopt what I term a ‘division of cognitive labor’ among models, using different models for the purposes of explanation and prediction, respectively, even for the exact same phenomenon being investigated. Adopting this strategy raises a number of issues, however, which have received inadequate philosophical attention. More specifically, while one implication (...) may be that it is inappropriate to judge explanatory models by the same standards of quantitative accuracy as predictive models, there still needs to be some way of either confirming or rejecting these model explanations. Here I argue that robustness analyses have a central role to play in testing highly idealized explanatory models. I illustrate these points with two examples of explanatory models from the field of geomorphology. (shrink)

The complex organization of syntax in hierarchical structures is one of the core design features of human language. Duality of patterning refers, for instance, to the organization of the meaningful elements in a language at two distinct levels: a combinatorial level, where meaningless forms are combined into meaningful forms; and a compositional level, where meaningful forms are composed into larger lexical units. The question remains wide open regarding how such structures could have emerged. The aim of this paper is to (...) address these two aspects in a self-consistent way. First, we introduce suitable measures to quantify the level of combinatoriality and compositionality in a language, and we present a framework to estimate these observables in human natural languages. Second, we show that a recently introduced multi-agent modeling scheme, namely the Blending Game, provides a mathematical framework to address the problem of how a population of individuals can bootstrap combinatoriality and compositionality. Theoretical predictions based on this model turn out to be in good agreement with empirical data. It is remarkable that the two sides of duality of patterning emerge simultaneously as a consequence of a pure cultural dynamics in a simulated environment that contains meaningful relations, provided a simple constraint on message transmission fidelity is also considered. (shrink)

The paper explicates the stages of the author’s philosophical evolution in the light of Kopnin’s ideas and heritage. Starting from Kopnin’s understanding of dialectical materialism, the author has stated that category transformations of physics has opened from conceptualization of immutability to mutability and then to interaction, evolvement and emergence. He has connected the problem of physical cognition universals with an elaboration of the specific system of tools and methods of identifying, individuating and distinguishing objects from a scientific theory domain. The (...) role of vacuum conception and the idea of existence (actual and potential, observable and nonobservable, virtual and hidden) types were analyzed. In collaboration with S.Crymski heuristic and regulative functions of categories of substance, world as a whole as well as postulates of relativity and absoluteness, and anthropic and self-development principles were singled out. Elaborating Kopnin’s view of scientific theories as a practically effective and relatively true mapping of their domains, the author in collaboration with M. Burgin have originated the unified structure-nominative reconstruction (model) of scientific theory as a knowledge system. According to it, every scientific knowledge system includes hierarchically organized and complex subsystems that partially and separately have been studied by standard, structuralist, operationalist, problem-solving, axiological and other directions of the current philosophy of science. 1) The logico-linguistic subsystem represents and normalizes by means of different, including mathematical, languages and normalizes and logical calculi the knowledge available on objects under study. 2) The model-representing subsystem comprises peculiar to the knowledge system ways of their modeling and understanding. 3) The pragmatic-procedural subsystem contains general and unique to the knowledge system operations, methods, procedures, algorithms and programs. 4) From the viewpoint of the problem-heuristic subsystem, the knowledge system is a unique way of setting and resolving questions, problems, puzzles and tasks of cognition of objects into question. It also includes various heuristics and estimations (truth, consistency, beauty, efficacy, adequacy, heuristicity etc) of components and structures of the knowledge system. 5) The subsystem of links fixes interrelations between above-mentioned components, structures and subsystems of the knowledge system. The structure-nominative reconstruction has been used in the philosophical and comparative case-studies of mathematical, physical, economic, legal, political, pedagogical, social, and sociological theories. It has enlarged the collection of knowledge structures, connected, for instance, with a multitude of theoreticity levels and with an application of numerous mathematical languages. It has deepened the comprehension of relations between the main directions of current philosophy of science. They are interpreted as dealing mainly with isolated subsystems of scientific theory. This reconstruction has disclosed a variety of undetected knowledge structures, associated also, for instance, with principles of symmetry and supersymmetry and with laws of various levels and degrees. In cooperation with the physicist Olexander Gabovich the modified structure-nominative reconstruction is in the processes of development and justification. Ideas and concepts were also in the center of Kopnin’s cognitive activity. The author has suggested and elaborated the triplet model of concepts. According to it, any scientific concept is a dependent on cognitive situation, dynamical, multifunctional state of scientist’s thinking, and available knowledge system. A concept is modeled as being consisted from three interrelated structures. 1) The concept base characterizes objects falling under a concept as well as their properties and relations. In terms of volume and content the logical modeling reveals partially only the concept base. 2) The concept representing part includes structures and means (names, statements, abstract properties, quantitative values of object properties and relations, mathematical equations and their systems, theoretical models etc.) of object representation in the appropriate knowledge system. 3) The linkage unites a structures and procedures that connect components from the abovementioned structures. The partial cases of the triplet model are logical, information, two-tired, standard, exemplar, prototype, knowledge-dependent and other concept models. It has introduced the triplet classification that comprises several hundreds of concept types. Different kinds of fuzziness are distinguished. Even the most precise and exact concepts are fuzzy in some triplet aspect. The notions of relations between real scientific concepts are essentially extended. For example, the definition and strict analysis of such relations between concepts as formalization, quantification, mathematization, generalization, fuzzification, and various kinds of identity are proposed. The concepts «PLANET» and «ELEMENTARY PARTICLE» and some of their metamorphoses were analyzed in triplet terms. The Kopnin’s methodology and epistemology of cognition was being used for creating conception of the philosophy of law as elaborating of understanding, justification, estimating and criticizing legal system. The basic information on the major directions in current Western philosophy of law (legal realism, feminism, criticism, postmodernism, economical analysis of law etc.) is firstly introduced to the Ukrainian audience. The classification of more than fifty directions in modern legal philosophy is suggested. Some results of historical, linguistic, scientometric and philosophic-legal studies of the present state of Ukrainian academic science are given. (shrink)

The construction projects in Pakistan have inherent problems of erroneous planning and schedule development. This dilemma has led to the failure of the majority of construction projects in Pakistan. Earlier researches have tried to curtail the increasing spectrum of inaccurate planning and schedule development. But not many research studies have shed light on the major factor of 2D CAD drawings interpretation problems, which are playing a key role in defective planning and scheduling. Moreover, the role of BIM, i.e., Building Information (...) Modeling with respect to efficient planning, has not been also discussed in detail. This study has concluded a positive impact of BIM on effective planning and scheduling in the construction industry of Pakistan. About 210 responses were obtained from experienced construction professionals of Pakistan and tested via regression analysis in order to validate this argument. It has been analyzed that 2D CAD drawings are now getting primitive and 3D technology BIM is taking its place. BIM is an efficient tool for planning and scheduling. With the start of CPEC and Multi-Billion Dollar investment on infrastructure, construction industry of Pakistan needs to uplift its existing standard in order to meet with international requirements. For this purpose, BIM has been recommended. It will not only assist in attaining flawless planning but will also increase the success rate of CPEC projects in Pakistan. (shrink)

Global environmental problems, such as global warming, pollution, or deforestation, are critical issues that require a rapid and common response. In this context, companies play a decisive role in achieving environmental objectives through the ecological knowledge they can store and manage. In this context, the present research focuses its interest on analyzing how the set of green intangibles possessed by organizations, i.e., Green Intellectual Capital, affects their Green Performance. Specifically, the study shows how GP is influenced by GIC through the (...) mediating role of the Green Innovation variable. Therefore, the research questions to be answered by this study are as follows: Does GIC influence environmental performance? Does GI mediate the GIC-GP relationship? What actions can companies take to improve their GP? There are several reasons that have led us to carry out this research. First, there is little empirical evidence of the relationships proposed in this study. Second, to the best of our knowledge, there is no previous research that has contextualized the relationships raised in the wine industry, thus representing an advance in the comprehension of the constructs studied. Third, GIC represents an incipient field of study that needs to be developed and established within the literature linked to Intellectual Capital. In order to achieve the proposed objectives, data from a survey of 202 wineries in Spain were used and a quantitative approach was followed using Structural Equation Modeling. The results of the research indicate that there is a positive and significant relationship between GIC and GP. In addition, GI partially mediates the relationship between these two variables, playing a key role in the environmental management of wineries. The theoretical and practical contributions of the study improve the understanding of the relationships raised, being a pioneering study due to its contextualization in the wine industry, as well as providing a series of guidelines for both environmental managers and winemakers to improve their GP. (shrink)

Enzymatic misrepair of ionizing‐radiation‐induced DNA damage can produce large‐scale rearrangements of the genome, such as translocations and dicentrics. These and other chromosome exchange aberrations can cause major phenotypic alterations, including cell death, mutation and neoplasia. Exchange formation requires that two (or more) genomic loci come together spatially. Consequently, the surprisingly rich aberration spectra uncovered by recently developed techniques, when combined with biophysically based computer modeling, help characterize large‐scale chromatin architecture in the interphase nucleus. Most results are consistent with a (...) picture whereby chromosomes are mainly confined to territories, chromatin motion is limited, and interchromosomal interactions involve mainly territory surfaces. Aberration spectra and modeling also help characterize DNA repair/misrepair mechanisms. Quantitative results for mammalian cells are best described by a breakage‐and‐reunion model, suggesting that the dominant recombinational mechanism during the G0/G1 phase of the cell cycle is non‐homologous end‐joining of radiogenic DNA double strand breaks. In turn, better mechanistic and quantitative understanding of aberration formation gives new insights into health‐related applications. BioEssays 24:714–723, 2002. © 2002 Wiley Periodicals, Inc. (shrink)

Lewis proposes a “reconceptualization” of how to link the psychology and neurobiology of emotion and cognitive-emotional interactions. His main proposed themes have actually been actively and quantitatively developed in the neural modeling literature for more than 30 years. This commentary summarizes some of these themes and points to areas of particularly active research in this area.

Currently, the widely used notion of activity is increasingly present in computer science. However, because this notion is used in specific contexts, it becomes vague. Here, the notion of activity is scrutinized in various contexts and, accordingly, put in perspective. It is discussed through four scientific disciplines: computer science, biology, economics, and epistemology. The definition of activity usually used in simulation is extended to new qualitative and quantitative definitions. In computer science, biology and economics disciplines, the new simulation activity (...) definition is first applied critically. Then, activity is discussed generally. In epistemology, activity is discussed, in a prospective way, as a possible framework in models of human beliefs and knowledge. (shrink)

Bioscientists generate far more data than their minds can handle, and this trend is likely to continue. With the aid of a small set of versatile tools for mathematical modeling and statistical assessment, bioscientists can explore their real-world systems without experiencing data overflow. This article outlines an approach for combining modern high-throughput, low-cost, but non-selective biospectroscopy measurements with soft, multivariate biochemometrics data modeling to overview complex systems, test hypotheses, and making new discoveries. From preliminary, broad hypotheses and goals, (...) many relevant samples are selected and measured with respect to many informative variables. The resulting tables represent a “cacophony” of data. From these, the most relevant and reliable “underlying harmonies and rhythms” are extracted and tested statistically, displayed for interpretation, and used for prediction. Outliers are detected automatically. Interesting subsets of samples can then be chosen for in-depth analyses in subsequent research cycles. This pragmatic, top-down approach takes advantage of developments in both “soft,” data-driven modeling and “hard,” knowledge-driven cultures. Data analytical examples show how information-rich biospectroscopy can be used for characterizing and quantifying known and unknown chemical constituents and physical phenomena in intact biosamples. This is based on a combination of deductive “hard” and inductive “soft” modeling. The examples represent NIR spectra of biochemical mixtures, FTIR spectra of a microbiological fermentation process, and FTIR analysis of fatty acids in milk for functional genomics. (shrink)

Due to the introduction of memristors, the memristor-based nonlinear oscillator circuits readily present the state initial-dependent multistability, i.e., coexisting multiple attractors. The dimensionality reduction modeling for a memristive circuit is carried out to realize accurate prediction, quantitative analysis, and physical control of its multistability, which has become one of the hottest research topics in the field of information science. Based on these considerations, this paper briefly reviews the specific multistability phenomenon generating from the memristive circuit in the voltage-current (...) domain and expounds the multistability control strategy. Then, this paper introduces the accurate flux-charge constitutive relation of memristors. Afterwards, the dimensionality reduction modeling method of the memristive circuits, i.e., the incremental flux-charge analysis method, is emphatically introduced, whose core idea is to implement the explicit expressions of the initial conditions in the flux-charge model and to discuss the feasibility and effectiveness of the multistability reconstitution of the memristive circuits using their flux-charge models. Furthermore, the incremental integral transformation method for modeling of the memristive system is reviewed by following the idea of the incremental flux-charge analysis method. The theory and application promotion of the dimensionality reduction modeling and multistability reconstitution are proceeded, and the application prospect is prospected by taking the synchronization application of the memristor-coupled system as an example. (shrink)

Specific classes of cyberspaces emphasize different types of digital transactions given the user’s context, thus making it essential to take into account what these environments can afford. In this way, we can portray the niches of technological use as ecologies of particular possibilities and compare how they differ between distinct spheres of human life. The present research is focused on describing the conceptual integration of a taxonomic crossover between Virtual Learning Environments and Educational Affordances of Technology, while also performing empirical (...) testing and determining the psychometric properties in a scale regarding the aforementioned taxonomy. The study sample consisted of 320 students in the departments of foreign languages from three different universities in Sonora. Students were given a questionnaire of 21 items organized into four subscales with a Likert-type response option to measure the notions concerning their usage of Virtual Learning Environments. Internal consistency procedures and confirmatory factor analysis by means of Cronbach’s alpha and Structural modeling support the derived factorial structure, which contains Cyber-Communications, Virtual Behavior Settings, Virtual Communities, and Availability and Access to Connectivity. This structure traces the environmental properties perceived by learners in a virtual environment. Results sustain the initial conceptual construction regarding the proposed taxonomy, conclude that the ‘Virtual Learning Environments Questionnaire’ demonstrates adequate psychometric properties, and validate it as a fitting measure to assess the perceived psychological experience of students in a digital educational setting. (shrink)

In this article, we tried to reveal the relationship between personality traits and escape behavior in traffic accidents. Different from common computer simulations, this study, for the first time, established a real database recording the escape behavior and personality traits of subjects when watching a first-person-view driving video with explosion. Then, we used a modeling method of general linear to establish a quantitative model of the influence of personality traits, explosion, and their interaction on escape behavior. In the (...) model, we introduced escape response time, escape time, escape direction, escape speed, escape trajectory, and other motion characteristics to study individual escape behavior in accidents. Through the analysis, we concluded several conclusions, including that high neurotic individuals tend to escape with shorter response time and slower speed by choosing doors far from the explosion source. These conclusions may provide some references for the effective escape of the crowd and the successful escape of the individual under traffic accidents. (shrink)