Invalid Model Research Articles

ABCA1, from pathology to membrane function

The ABCA1 transporter is the prototype of the A class of mammalian adenosine triphosphate binding cassette transporters and one of the largest members of this family. ABCA1 has been originally identified as an engulfment receptor on macrophages and, more recently, it has been shown to play an essential role in the handling of cellular lipids. Indeed by promoting the effluxes of membrane phospholipids and cholesterol to lipid-poor apoprotein acceptors, ABCA1 controls the formation of high-density lipoproteins and thus the whole process of reverse cholesterol transport. A number of additional phenotypes have been found in the mouse model of invalidation of the ABCA1 gene. In spite of their clinical diversity, they all are extremely sensitive to variations in the physicochemical properties of the cell membrane, which ABCA1 controls as a lipid translocator.

Validity of fixing a zero forming electrode at a non-Pierce angle for optimization of a highly compressed electron beam

Substantiation of applying a zero forming electrode with a non-Pierce angle for optimal beam compression is shown to rely on an invalid theoretical model, the use of which may lead to a confusing situation in which the intrinsic properties of the calculation algorithm are analyzed rather than the real physics of the phenomenon under investigation.

A Fault Identification Algorithm for Satellite Networks Based on System Level Diagnosis

It is a challenge to support the fault tolerance for satellite networks, in which fault identification is primary. After modeling satellite networks with two-level-node graph, a fault identification algorithm based on PMC test invalidation model is presented and proved to be correct. The effectiveness of the algorithm in different types of satellite networks is compared and studied by simulations. The results of experiments illustrate that the

Model Validation: Model Parameter and Measurement Uncertainty

Our increased dependence on complex models for engineering design, coupled with our decreased dependence on experimental observation, leads to the question: How does one know that a model is valid? As models become more complex (i.e., multiphysics models), the ability to test models over the full range of possible applications becomes more difficult. This difficulty is compounded by the uncertainty that is invariably present in the experimental data used to test the model; the uncertainties in the parameters that are incorporated into the model; and the uncertainties in the model structure itself. Here, the issues associated with model validation are discussed and methodology is presented to incorporate measurement and model parameter uncertainty in a metric for model validation through a weighted r2 norm. The methodology is based on first-order sensitivity analysis coupled with the use of statistical models for uncertainty. The result of this methodology is compared to results obtained from the more computationally expensive Monte Carlo method. The methodology was demonstrated for the nonlinear Burgers’ equation, the convective-dispersive equation, and for conduction heat transfer with contact resistance. Simulated experimental data was used for the first two cases, and true experimental data was used for the third. The results from the sensitivity analysis approach compared well with those for the Monte Carlo method. The results show that the metric presented can discriminate between valid and invalid models. The metric has the advantage that it can be applied to multivariate, correlated data.

Raiders of the Lost Vote: A Theory-Driven Model of Ballot Invalidation in Florida's 2000 Election

In analyzing the results of the 2000 Florida election, we argue the need for a more theoretical model of ballot invalidation. The majority of studies to date link together both undervotes and overvotes into one measure of “rejected,” “voided” or “invalidated” ballots. We demonstrate that these two types of errors are notably distinct. Specifically, overvoting involves more cognitive or “decision” errors, while undervoting is more a product of mechanical or “physical” errors. As such, we maintain that undervotes are more likely to be the product of random error and are less likely to be related to the racial composition of a district than are overvotes.

Econometric Models for Marketing Decisions

ance of aggregation biases, and so on. Franses (2005) provides an inventory of commonly used diagnostic tests. Franses (see Table 2 for 1998–2000 and Table 3 for 2001– 2003) also shows that there is a paucity of actual use of diagnostic tests in articles published in JMR. Such paucity may suggest that researchers have a disincentive to conduct all relevant tests. For example, it might be imagined that though researchers prefer to publish a valid model rather than one that is invalid, publishing an invalid model is still preferred to not publishing one, especially if it is difficult for readers to detect model deficiencies. Given data constraints, it is virtually impossible for researchers to accommodate all possible nuances. Thus, researchers rely on theories and experience to decide which aspects are the most critical to include in a model. With accumulating empirical evidence in the literature, the expectation is that future modeling efforts will be more informed and thus likely to provide increasingly useful (i.e., valid and reliable) results. However, I urge researchers to consult the checklist that Franses provides and to conduct all diagnostic tests when appropriate. In applied econometrics, there are three possible reasons for specific tests not to be used. First, researchers may argue convincingly that a test does not apply in the model’s context. For example, testing the null hypothesis of zero autocorrelation in the error term in a model of purely cross-sectional data is irrelevant. (Separately, I note that the use of generalized least squares rather than ordinary least squares to accommodate serial correlation in time series data is a technical correction that is not convincing unless the researcher can justify how serial correction logically arises for an otherwise correctly specified model.) Second, some tests may not yet be available for cases other than linear models and normally distributed errors. Third, researchers may argue that the violation of a particular assumption does not invalidate the substantive results. For example, consistency of ordinary least squares does not require normality of the error term. In all other cases, it is the researchers’ responsibility to conduct and show appropriate diagnostic tests. The model cannot be assumed to be valid unless proper diagnostic tests fail to reject the assumptions. Because all models are incomplete representations of reality, a central question is: How can a model that is superior to a meaningful alternative (e.g., judgment or a simpler representation than the proposed model) be obtained? If the interest of the researcher is to discover how marketing activities affect purchases or other responses (as in a “causal” model), any comparison to a model without marketing variables seems useless. Still, it might be argued that Beginning with the August 2003 issue, Journal of Marketing Research (JMR) has published one or more comments on the lead article, followed by a rejoinder. I have asked experts to provide commentary on one article in each issue that I believe has especially relevant content for researchers and managers. In the current issue, the lead article is an invited paper for which I also asked several experts to provide comments. In all cases, I provide an opportunity for the author(s) of the original article to prepare a rejoinder in the same issue. My hope is that such related reflections and commentaries on a current topic will enhance the value of JMR to readers. Although I see no reason to entice authors to express strong disagreements about specific issues, I expect that such collections of articles will enable readers to become more informed about differences in perspectives that researchers with substantial expertise and experience have on important issues.

Colorectal cancers in a new mouse model of familial adenomatous polyposis: influence of genetic and environmental modifiers

Murine models of familial adenomatous polyposis harbor a germinal heterozygous mutation on Apc tumor suppressor gene. They are valuable tools for studying intestinal carcinogenesis, as most human sporadic cancers contain inactivating mutations of APC. However, Apc+/− mice, such as the well-characterized ApcMin/+ model, develop cancers principally in the small intestine, while humans develop mainly colorectal cancers. We used a Cre-loxP strategy to achieve a new model of germline Apc invalidation in which exon 14 is deleted. We compared the phenotype of these ApcΔ14/+ mice to that of the classical ApcMin/+. The main phenotypic difference is the shift of the tumors in the distal colon and rectum, often associated with a rectal prolapse. Thus, the severity of the colorectal phenotype is partly due to the particular mutation Δ14, but also to environmental parameters, as mice raised in conventional conditions developed more colon cancers than those raised in pathogen-free conditions. All lesions, including early lesions, revealed Apc LOH and loss of Apc gene expression. They accumulated β-catenin, overexpressed the β-catenin target genes cyclin D1 and c-Myc, and the distribution pattern of glutamine synthetase, a β-catenin target gene recently identified in the liver, was mosaic in intestinal adenomas. The ApcΔ14/+ model is thus a useful new tool for studies on the molecular mechanisms of colorectal tumorigenesis.

Just say no to psychotropic drugs!

Prescribing drugs for mental disorders by psychologists means accepting an invalid model--the brain disease, biological-defect explanation of psychopathology--that is advanced by political conservatives and accepted by some naive, well-intentioned, but misinformed moderates who have not thought critically about the issue. Conservative psychiatry serves the ruling class by rejecting or ignoring the fact that most mental disorders are learned in the context of social and economic injustice, and familiar dysfunction. If we accept the fallacy of brain disease and genetic defect as the major causes of mental disorder and succeed in getting prescription privileges we will have sold our soul to the devil!

Rat adrenal transplants are reinnervated: an invalid model of denervated adrenal cortical tissue.

Adrenal autotransplantation is a widely used approach to investigate the potential for neural modulation of adrenal cortical function. It is believed that regenerating adrenal transplants are not reinnervated, thereby providing a model to investigate adrenal function in the absence of neural modulation. However, the hypothesis that adrenal transplants become reinnervated has not been directly tested. The purpose of the present study was to characterize the time course, extent, and nature of the reinnervation of the regenerating adrenal transplant and to assess whether the recovery of steroidogenic function and enzyme expression correlates temporally with the presence of innervation. Using immunohistofluorescent detection of tyrosine hydroxylase (TH), neuropeptide Y (NPY), calcitonin gene-related peptide (CGRP), and vasoactive intestinal peptide (VIP), the innervation of regenerating adrenals was assessed 14-30 days after transplantation of adrenal capsules beneath the kidney capsule in rats. Extensive reinnervation by TH-, NPY-, and VIP-positive fibres was present by 14 days after transplantation including regions of the adrenal capsule and cortex, with only minimal reinnervation by CGRP-positive fibres up to 30 days. TH- and NPY-positive chromaffin cells were also observed in the regenerating transplants. In addition, there was marked recovery of steroidogenic function and steroidogenic enzyme expression up to 30 days. The finding that nerve fibres are present in the transplants during the re-establishment of steroidogenic function and enzyme expression suggests that innervation may modulate the regeneration and functional recovery of adrenal transplants. In an attempt to prevent reinnervation of transplants, adrenal capsules were autotransplanted to denervated kidneys. Immunohistochemical analysis showed that, despite extensive denervation of the kidney tissue, the reinnervation and regeneration of the adrenal transplants still occurred. These data demonstrate the marked capacity of the regenerating adrenal to become reinnervated and reinforces the conclusion that adrenal transplants are an invalid model of denervated adrenal cortical tissue.

Building competitive advantage from ubuntu: Management lessons from South Africa

Executive Overview Much of management theory is based on the writings of early 20th-century Western scholars whose disciplinary orientations were heavily grounded in economics and classical sociology. These writings depict homo sapiens as an individualistic, utility-maximizing, transaction-oriented species. In contrast, recent scholarship has revealed the gender and racio-ethnic biases of these theories, and shown them to be invalid models of human nature. Humans are social and communal beings. Along with rationality, we are guided by emotions such as anxiety, hope, disappointment, fear, anger, excitement, pity, and remorse. By acknowledging the importance of emotions, world management discourse can evolve more holistic, inclusive, and emancipatory theories. South Africa offers a unique opportunity for understanding the African concept of ubuntu or humaneness. Ubuntu is rich with consideration for compassion and communality. This article discusses the characteristics of ubuntu, explores situations in which it manifests itself in the workplace, and argues that ubuntu can give competitive advantage to companies that incorporate its principles and practices.

Regulation and Role of Adenylyl Cyclase Isoforms

At least nine closely related isoforms of adenylyl cyclases (ACs), the enzymes responsible for the synthesis of cyclic AMP (cAMP) from ATP, have been cloned and characterized in mammals. Depending on the properties and the relative levels of the isoforms expressed in a tissue or a cell type at a specific time, extracellular signals received through the G-protein-coupled receptors can be differentially integrated. The present review deals with various aspects of such regulations, emphasizing the role of calcium/calmodulin in activating AC1 and AC8 in the central nervous system, the potential inhibitory effect of calcium on AC5 and AC6, and the changes in the expression pattern of the isoforms during development. A particular emphasis is given to the role of cAMP during drug and ethanol dependency and to some experimental limitations (pitfalls in the interpretation of cellular transfection, scarcity of the invalidation models, existence of complex macromolecular structures, etc).

Tissue specificity and physiological relevance of various isoforms of adenylyl cyclase.

The present review focuses on the potential physiological regulations involving different isoforms of adenylyl cyclase (AC), the enzymatic activity responsible for the synthesis of cAMP from ATP. Depending on the properties and the relative level of the isoforms expressed in a tissue or a cell type at a specific time, extracellular signals received by the G protein-coupled receptors can be differently integrated. We report here on various aspects of such regulations, emphasizing the role of Ca(2+)/calmodulin in activating AC1 and AC8 in the central nervous system, the potential inhibitory effect of Ca(2+) on AC5 and AC6, and the changes in the expression pattern of the isoforms during development. A particular emphasis is given to the role of cAMP during drug dependence. Present experimental limitations are also underlined (pitfalls in the interpretation of cellular transfection, scarcity of the invalidation models, and so on).

Representational validity of boundary representation models

Validity is an important property of solid modeling representations. It ensures that representations always describe physically realizable solids, instead of nonsense objects. This paper surveys and supplements the mathematical theory of ideal boundary representation (B-rep) of solids. In particular, it presents a complete set of conditions on representational nodes of a typical B-rep data structure and proves their sufficiency for model validity. Such conditions are useful in invalid model rectification procedures.

P—T—t—deformation—fluid characteristics of lode gold deposits: evidence from alteration systematics

P—T—t—deformation—fluid characteristics of lode gold deposits: evidence from alteration systematics

Effective prescribing at practice level should be identified and rewarded

In the administrative corridors of the European Union there is no longer any talk of cows, sheep, or pigs but only of “grain consuming units” or GCUs. A similar level...

Modeling error identification of activated sludge models

Information about the location of modeling erros is crucial for the efficient improvement of an invalid model. This article discusses how to pinpoint modeling errors through comparison of experimental data with data obtained through simulation of the invalid model. An observer-based approach is presented. By designing a dedicated observer for the system using the invalid model, a signal vector is generated, on which each modeling error imposes an easily identifiable feature. An algorithm to analyze the featured signal is then presented. With this algorithm, the features of each of the modeling errors are extracted. The approach is illustrated for a denitrification reactor model in which errors in the dimension of the state vector, in the structure of the biokinetic relationship and in the values of the parameters could be identified.

Modeling error identification of activated sludge models

Information about the location of modeling errors is crucial for the efficient improvement of an invalid model. This article discusses how to pinpoint modeling errors through comparison of experimental data with data obtained through simulation of the invalid model. An observer-based approach is presented. By designing a dedicated observer for the system using the invalid model, a signal vector is generated, on which each modeling error imposes an easily identifiable feature. An algorithm to analyze the featured signal is then presented. With this algorithm, the features of each of the modeling errors are extracted. The approach is illustrated for a denitrification reactor model in which errors in the dimension of the state vector, in the structure of the biokinetic relationship and in the values of the parameters could be identified.

Weighted diagnosis with asymmetric invalidation

Prior research has extended the classical PMC (or Symmetric Invalidation) Model to incorporate a priori weights or probabilities associated with units. We consider a similar extension to the BGM (or Asymmetric Invalidation) Model. In contrast to the PMC model, where deciding the weighted diagnosability number is co-NP complete, we show that the diagnosability number in the weighted BGM model can be obtained in O(m/sup 2/) time, where m is the number of tests in the system. We also show that diagnosis in this weighted model can be performed in O(T(n)) time, where n is the number of units in the system and T(n)/spl ap/n/sup 2.376/ is the amount of time needed to multiply two n by n matrices.

SMOES: a simulation model for the Oosterschelde ecosystem

SMOES is an invalid model in the Popperian sense of the word. Yet it might be a useful model, which accurately simulates some of the ecosystem behavior. Our knowledge of the Oosterschelde ecosystem is empirical and consists of a comprehensive set of observed data (experiments and in situ measure­ ments). Model usefulness will be investigated in terms of model adequacy (can a model simulate all system behavior) and reliability (does it simulate observed system behavior only). The large impact of the building of a storm-surge barrier in the Oosterschelde Mouth (compartment West) allows us to distinguish two different systems. The quality of the simulation model, built and calibrated for the pre-barrier system, can so be tested by using it for the (new) post-barrier system. The question if the model does predict the post-barrier future will be answered. We apply a calibration method which generates not merely a single best value for each of the many badly known parameters, but which also enables us to estimate the uncertainty in the model outcome. If we use this method to calibrate SMOES for the pre- and for the post-barrier situation, and sub­ sequently estimate the uncertainty in the model results, we find no large (functional) shifts in the behavior of the main ecosystem properties.

Perceptual integration in heterogeneous taste percepts.

When mixtures of dissimilar tasting compounds are perceived, specific taste sensations are integrated into a percept. Four models are evaluated that were designed to predict the total taste intensity of a mixture percept from the total taste intensities of the unmixed components or from the specific taste intensities of the components within the mixture percept. The predictions of the two dominant component models are inferior to those made by the two other models. Predictions made by the vector summation model are accurate, but the model contains theoretical weaknesses that make it an invalid psychological integration model. The sum of sensations model predicts total intensity with an accuracy similar to the vector summation model, but it is more parsimonious. Furthermore, it can account for all of the empirical phenomena observed.