Simple Graphical Model Research Articles

Modeling Neurodegeneration and Regeneration in Parkinson's Disease

The diagnosis and prevention of neurodegenerative diseases is a heavily examined topic in the neuroscience discipline. Whether it be from the anatomical and biological perspectives or the psychological and sociological perspectives, the ultimate goal is to discover strategies to pinpoint the infection as soon as possible. This article begins with reviewing the small-world network structure and then combines the sociological and anatomical perspectives to explain the progression of neuronal death within the brain by using rsfMRI data and the Hegselmann-Krause Model of Opinion Dynamics to illustrate critical interactions between brain regions, and to predict the ultimate behavior of the neural network after initial degeneration Following experimentation–in which critical regions related to Parkinson’s Disease were studied–thresholds were identified in specific regions which exhibited consistent converging behavior of the neural network toward either degenerative or regenerative directions. Furthermore, a simple graphical model is proposed to demonstrate the ranges of values in which current brain health could be of concern. We concluded that neuron death in one brain region can lead to further infection in the resulting system; however, some regions can also directly/indirectly compensate for the system’s decreased function. In future research endeavors, this could provide insight into developing more accurate predictive models for the goal of early detection of a diseased brain and its recovery.

Evolutionary game theory to predict the population growth in Few districts of Tamil Nadu and Kerala

The conventional models in Game Theory focuses entirely on the relative fitness of the population agents leaving the dynamic behaviour of the size of population left uncovered. Therefore, a robust model is required to combine both the growth dynamics and internal evolution of agents. Evolutionary Game Theory to Predict the Population Growth in Few Districts of Tamil Nadu and Kerala. In this paper, we develop an Evolutionary Game Theory (EGT) model which is integrated with the Residual deterministic learning (RDL) model to increase the rate of prediction of the population growth. Various deterministic models including Arithmetic Increase, Geometric Increase, Incremental Increase and Simple graphical models are used to improve the prediction ability of EGT. The EGT combined with RDL forms REGT model that is found scalable to predict the long-term population growth in near proximal districts of Tamil Nadu and Kerala. Various inputs affecting the population growth are considered as the inputs to the REGT model to the Matlab simulator. The experimentation shows that the proposed REGT model is better in predicting the population growth than the existing game theory models.

Quantum Markov chain Monte Carlo with digital dissipative dynamics on quantum computers

Modeling the dynamics of a quantum system connected to the environment is critical for advancing our understanding of complex quantum processes, as most quantum processes in nature are affected by an environment. Modeling a macroscopic environment on a quantum simulator may be achieved by coupling independent ancilla qubits that facilitate energy exchange in an appropriate manner with the system and mimic an environment. This approach requires a large, and possibly exponential number of ancillary degrees of freedom which is impractical. In contrast, we develop a digital quantum algorithm that simulates interaction with an environment using a small number of ancilla qubits. By combining periodic modulation of the ancilla energies, or spectral combing, with periodic reset operations, we are able to mimic interaction with a large environment and generate thermal states of interacting many-body systems. We evaluate the algorithm by simulating preparation of thermal states of the transverse Ising model. Our algorithm can also be viewed as a quantum Markov chain Monte Carlo process that allows sampling of the Gibbs distribution of a multivariate model. To demonstrate this we evaluate the accuracy of sampling Gibbs distributions of simple probabilistic graphical models using the algorithm.

A graphical null model for scaling biodiversity–ecosystem functioning relationships

AbstractGlobal biodiversity is declining at rates faster than at any other point in human history. Experimental manipulations at small spatial scales have demonstrated that communities with fewer species consistently produce less biomass than higher diversity communities. Understanding the consequences of the global extinction crisis for ecosystem functioning requires understanding how local experimental results are likely to change with increasing spatial and temporal scales and from experiments to naturally assembled systems.Scaling across time and space in a changing world requires baseline predictions. Here, we provide a graphical null model for area scaling of biodiversity–ecosystem functioning relationships using observed macroecological patterns: the species–area curve and the biomass–area curve. We use species–area and biomass–area curves to predict how species richness–biomass relationships are likely to change with increasing sampling extent. We then validate these predictions with data from two naturally assembled ecosystems: a Minnesota savanna and a Panamanian tropical dry forest.Our graphical null model predicts that biodiversity–ecosystem functioning relationships are scale‐dependent. However, we note two important caveats. First, our results indicate an apparent contradiction between predictions based on measurements in biodiversity–ecosystem functioning experiments and from scaling theory. When ecosystem functioning is measured as per unit area (e.g. biomass per m2), as is common in biodiversity–ecosystem functioning experiments, the slope of the biodiversity ecosystem functioning relationship should decrease with increasing scale. Alternatively, when ecosystem functioning is not measured per unit area (e.g. summed total biomass), as is common in scaling studies, the slope of the biodiversity–ecosystem functioning relationship should increase with increasing spatial scale. Second, the underlying macroecological patterns of biodiversity experiments are predictably different from some naturally assembled systems. These differences between the underlying patterns of experiments and naturally assembled systems may enable us to better understand when patterns from biodiversity–ecosystem functioning experiments will be valid in naturally assembled systems.Synthesis. This paper provides a simple graphical null model that can be extended to any relationship between biodiversity and any ecosystem functioning across space or time. Furthermore, these predictions provide crucial insights into how and when we may be able to extend results from small‐scale biodiversity experiments to naturally assembled regional and global ecosystems where biodiversity is changing.

The Parental Stress Scale revisited: Rasch-based construct validity for Danish parents of children 2\u201318\u2009years old with and without behavioral problems

BackgroundExperiencing parental stress is common among parents of children of all ages and is elevated in families characterized by stressors such as poverty, mental health problems, and developmental problems. The Parental Stress Scale (PSS) is a short measure for the assessment of perceived stress resulting from being a parent.MethodsThis study examines the construct validity and psychometric properties of the Danish PSS using Rasch and graphical loglinear Rasch models in a sample of parents of 2–18-year-old children with and without known behavior problems. We emphasized analyses of differential item functioning, to ascertain whether the scale yields unbiased scores for subgroups of parents.ResultsThe 18-item PSS did not fit the Rasch model or a graphical loglinear Rasch model. After dichotomizing item responses and eliminating items 2 and 11, we found the PSS to consist of two distinct subscales measuring parental stress and lack of parental satisfaction. For the total sample, the Parental Stress subscale fit a very complex graphical loglinear Rasch model with differential item functioning relative to parental education and whether children had behavior problems or not. The Lack of Parental Satisfaction subscale fit a simple graphical loglinear Rasch model with differential item functioning only relative to subsample. When dividing into subsamples of parents of children with and without behavior problems, the Parental Stress subscale fit a simple graphical loglinear Rasch model, though still with differential item functioning, while the Lack of Parental Satisfaction subscale fit the Rasch model in each subsample of parents. Both subscales performed best for parents of children with behavior problems.ConclusionsThe PSS should be used in a 16-item version and scored as two subscales. The PSS appears better suited for use among parents of children with behavior problems than within a sample without any known difficulties.

Democracy, Lobbying and Economics

Abstract The paper deals with the issue of lobbying, defined as a democratic means of promoting interests. The text tries to find answers to the problems in the current economic theory. The basic links are defined by using a simple graphic model, which are further examined by the SWOT analysis. The result is the knowledge that the basic coordination mechanism is the market – the information market. The role of government lies above all in creating a favourable institutional environment that does not interfere with spontaneous market relations. However, there are certain situations that the government could or should regulate. These situations are described by three hypothetical scenarios – a society without lobbying, a society where lobbing exists, but it is not transparent, and a society where lobbing is transparent, leading to a final discussion of possible directions and ways of its regulation.

RELIABILITY ASSESSMENT OF WOODEN TRUSSES OF A HISTORICAL SCHOOL

Records show that the National Structural Code of the Philippines (NSCP) wind load requirement increases over time. Increase wind velocity from stronger typhoon events translates to additional wind pressure. These changes pose a threat to existing historical structures such as Gabaldon schools which were designed and constructed more than a hundred years ago. The Department of Education (DepEd) continues its efforts in its conservation. Reliability assessment of wooden trusses is necessary to check if there is a need to retrofit to maintain its function and preserve its significance in the country’s history. In the analysis of the roof trusses affected directly by wind load, all loads are considered as constant except for the uniformly distributed wind load. These constant loads serve as the initial stresses acting within the truss members. Uniformly distributed wind load produces additional stress on top of the initial stress. Any changes in the amount of wind load constitute proportionally to changes in the stresses of truss members. A commercially available software makes it easier to identify corresponding stresses for several amounts of wind load. Using a spreadsheet, a simple graphical model and equation are generated expressing the relationship between wind velocities against axial force, shear force and bending moment. Mechanical properties of wood establish the limits of its strength in terms of wind velocity using the graphical model and equation obtained. The result reveals the limitation of each truss member in terms of wind velocity that even ordinary people can now easily perceived and understood.

GPU-accelerated hierarchical Bayesian estimation of luminosity functions using flux-limited observations with photometric noise

We describe a computational framework for hierarchical Bayesian inference with simple (typically single-plate) parametric graphical models that uses graphics processing units (GPUs) to accelerate computations, enabling deployment on very large datasets. Its C++ implementation, CUDAHM (CUDA for Hierarchical Models) exploits conditional independence between instances of a plate, facilitating massively parallel exploration of the replication parameter space using the single instruction, multiple data architecture of GPUs. It provides support for constructing Metropolis-within-Gibbs samplers that iterate between GPU-accelerated robust adaptive Metropolis sampling of plate-level parameters conditional on upper-level parameters, and Metropolis-Hastings sampling of upper-level parameters on the host processor conditional on the GPU results. CUDAHM is motivated by demographic problems in astronomy, where density estimation and linear and nonlinear regression problems must be addressed for populations of thousands to millions of objects whose features are measured with possibly complex uncertainties. We describe a thinned latent point process framework for modeling such demographic data. We demonstrate accurate GPU-accelerated parametric conditional density deconvolution for simulated populations of up to 300,000 objects in ~1 hour using a single NVIDIA Tesla K40c GPU. Supplementary material provides details about the CUDAHM API and the demonstration problem.

Why do things fall? How to explain why gravity is not a force

In most high school physics classes, gravity is described as an attractive force between two masses as formulated by Newton over 300 years ago. Einstein’s general theory of relativity implies that gravitational effects are instead the result of a ‘curvature’ of space-time. However, explaining why things fall without resorting to Newton’s gravitational force can be difficult. This paper introduces some simple graphical and visual analogies and models which are suitable for the introduction of Einstein’s theory of general relativity at a high school level. These models provide an alternative to Newton’s gravitational force and help answer the simple question: why do things fall?

High molar mass amphiphilic block copolymer enables alignment and dispersion of unfunctionalized carbon nanotubes in melt-drawn thin-films

To extensively control the nanofiller arrangement (location, orientation, shape) is still a bottleneck for multi-wall carbon nanotube (MWCNT) nanocomposites. Here, we demonstrate simultaneous control of alignment (orientation) and dispersion (location) of pristine, i.e., unfunctionalized MWCNTs using a high molar mass (HMM) amphiphilic block copolymer (BCP). We tested whether a HMM BCP in a selective solvent (i) disperses MWCNTs (ii) disperses MWCNTs by similar mechanisms to low molar mass BCPs and (iii) is melt-drawable to align the well dispersed MWCNTs. The dispersibility of MWCNTs within poly(styrene)-block-poly(2-vinylpyridine) (PS-b-P2VP) (M¯w≈500kg/mol) and its homopolymers in (non-)selective solvents was investigated by sedimentation experiments, transmission electron microscopy and visible/near-infrared spectroscopy. Through BCP micelle mediated steric stabilization, HMM PS-b-P2VP led to a highly stable MWCNT dispersion, which is explained in two simple graphical models. Using the melt-drawing technique, the well dispersed MWCNT/PS-b-P2VP dispersion was processed into a nanocomposite with a high degree of MWCNT alignment and dispersion. HMM BCPs are of significance for structural MWCNT/polymer nanocomposites, typically containing HMM polymers.

High prices for rare species can drive large populations extinct: the anthropogenic Allee effect revisited

Consumer demand for plant and animal products threatens many populations with extinction. The anthropogenic Allee effect (AAE) proposes that such extinctions can be caused by prices for wildlife products increasing with species rarity. This price-rarity relationship creates financial incentives to extract the last remaining individuals of a population, despite higher search and harvest costs. The AAE has become a standard approach for conceptualizing the threat of economic markets on endangered species. Despite its potential importance for conservation, AAE theory is based on a simple graphical model with limited analysis of possible population trajectories. By specifying a general class of functions for price-rarity relationships, we show that the classic theory can understate the risk of species extinction. AAE theory proposes that only populations below a critical Allee threshold will go extinct due to increasing price-rarity relationships. Our analysis shows that this threshold can be much higher than the original theory suggests, depending on initial harvest effort. More alarmingly, even species with population sizes above this Allee threshold, for which AAE predicts persistence, can be destined to extinction. Introducing even a minimum price for harvested individuals, close to zero, can cause large populations to cross the classic anthropogenic Allee threshold on a trajectory towards extinction. These results suggest that traditional AAE theory may give a false sense of security when managing large harvested populations.

Quantitative metrics for evaluating the phased roll-out of clinical information systems

ObjectivesWe introduce a novel quantitative approach for evaluating the order of roll-out during phased introduction of clinical information systems. Such roll-outs are associated with unavoidable risk due to patients transferring between clinical areas using both the old and new systems. MethodsWe proposed a simple graphical model of patient flow through a hospital. Using a simple instance of the model, we showed how a roll-out order can be generated by minimising the flow of patients from the new system to the old system. ResultsThe model was applied to admission and discharge data acquired from 37,080 patient journeys at the Churchill Hospital, Oxford between April 2013 and April 2014. The resulting order was evaluated empirically and produced acceptable orders. DiscussionThe development of data-driven approaches to clinical Information system roll-out provides insights that may not necessarily be ascertained through clinical judgment alone. Such methods could make a significant contribution to the smooth running of an organisation during the roll-out of a potentially disruptive technology. ConclusionUnlike previous approaches, which are based on clinical opinion, the approach described here quantitatively assesses the appropriateness of competing roll-out strategies. The data-driven approach was shown to produce strategies that matched clinical intuition and provides a flexible framework that may be used to plan and monitor Clinical Information System roll-out

Constrained Optimization Methods in Health Services Research-An Introduction: Report 1 of the ISPOR Optimization Methods Emerging Good Practices Task Force.

Providing health services with the greatest possible value to patients and society given the constraints imposed by patient characteristics, health care system characteristics, budgets, and so forth relies heavily on the design of structures and processes.Such problems are complex and require a rigorous and systematic approach to identify the best solution. Constrained optimization is a set of methods designed to identify efficiently and systematically the best solution (the optimal solution) to a problem characterized by a number of potential solutions in the presence of identified constraints. This report identifies 1) key concepts and the main steps in building an optimization model; 2) the types of problems for which optimal solutions can be determined in real-world health applications; and 3) the appropriate optimization methods for these problems. We first present a simple graphical model based on the treatment of "regular" and "severe" patients, which maximizes the overall health benefit subject to time and budget constraints. We then relate it back to how optimization is relevant in health services research for addressing present day challenges. We also explain how these mathematical optimization methods relate to simulation methods, to standard health economic analysis techniques, and to the emergent fields of analytics and machine learning.

Biased richness and evenness relationships within Shannon–Wiener index values

The purpose of this analysis was to empirically model and graphically illustrate the numerical relationships between richness (S, 4–35 species) and evenness (E) with respect to Shannon–Wiener index (H′, loge-based) values. Thirty-two richness-based third-order polynomial regression models (R>0.99, P<0.001, n=28–71) were constructed to characterize these relationships. A composite diagram showed richness varied curvilinearly, with steepness increasing and the spacing between curves decreasing with greater evenness and H′. Maximum H′ values for each richness curve were equal to logeS (when E=1), whereas minima were approximated by evenness values of ∼1/S (when H′=0). It was concluded from multiple and polynomial regression analyses that: (i) evenness contributed more than richness (E:S ≥3:1) to determining H′, based on standardized partial beta-coefficients; (ii) the differential in E:S ratios increased with greater richness; (iii) the patterns of H′ sample variation between maximum unevenness and perfect evenness was convexo-concave shaped; and (iv) richness as an explanatory variable of H′ was likely an artifact of evenness (0–1 scale) being rescaled according to individual H′ maxima. H′ was redefined as a logarithm-weighted measure of evenness at a given level of richness, which means H′ is either an imperfect index of diversity or a biased measure of evenness. It was also found that the fundamental components of the Shannon–Wiener index measure dominance concentration rather than evenness, with the reversal in emphasis due to multiplication of the H′ equation by −1. H′-derived effective species numbers (exp H′, D) increasingly deviated from those of the diversity model D=S×E in response to increasing richness (up to 69% for 35 species), particularly when evenness was between 0.15 and 0.40. Of two cross-validated H′ prediction methods (P<0.001, n=325), the collective use of individual richness-based polynomial regression equations (r=0.954) was better than a single multiple regression model that incorporated a broad spectrum of richness levels (r=0.882). A simple graphic model was constructed to illustrate patterns of evenness variation as a function of changing richness and H′ values. Based on the identified biases, particularly E:S ratios, it was recommended that use of H′ be discontinued as a basis for assessing diversity in ecological research or, at the very least, accompanied by independent analyzes of richness and evenness.

Nutritional integration between insect hosts and koinobiont parasitoids in an evolutionary framework

AbstractMark Jervis was one of the world's foremost experts on life history and development strategies in parasitoids. He held a special place for the nutritional ecology of immature and adult parasitoids; his work on adult nutritional ecology and reproduction is considered seminal. Here, we discuss aspects of parasitoid growth and development, focusing on species that attack feeding, growing hosts (so‐called koinobiont parasitoids). We provide a simple graphical model illustrating how selection pressures can alter host usage strategies, employing growth trajectories as a useful comparative tool. Furthermore, we discuss how the recent evolution of the hemolymph‐feeding strategy in koinobionts has enabled these parasitoids to greatly expand the suitable size range of hosts, as well as providing additional adaptive functions such as gregarious development, resource sharing, and the use of the dying host as a ‘bodyguard’ against predators and hyperparasitoids. Overall, we conclude that koinobionts exhibit a wide array of strategies in exploiting and utilizing variably sized hosts in response to a suite of quite divergent selection pressures that influence their growth, development, and survival.

Statistical Reasoning and Methods in Epidemiology to Promote Individualized Health: In Celebration of the 100th Anniversary of the Johns Hopkins Bloomberg School of Public Health.

Epidemiology is concerned with determining the distribution and causes of disease. Throughout its history, epidemiology has drawn upon statistical ideas and methods to achieve its aims. Because of the exponential growth in our capacity to measure and analyze data on the underlying processes that define each person's state of health, there is an emerging opportunity for population-based epidemiologic studies to influence health decisions made by individuals in ways that take into account the individuals' characteristics, circumstances, and preferences. We refer to this endeavor as "individualized health." The present article comprises 2 sections. In the first, we describe how graphical, longitudinal, and hierarchical models can inform the project of individualized health. We propose a simple graphical model for informing individual health decisions using population-based data. In the second, we review selected topics in causal inference that we believe to be particularly useful for individualized health. Epidemiology and biostatistics were 2 of the 4 founding departments in the world's first graduate school of public health at Johns Hopkins University, the centennial of which we honor. This survey of a small part of the literature is intended to demonstrate that the 2 fields remain just as inextricably linked today as they were 100 years ago.

Learning Mechanical Vibrations with Wolfram Mathematica

Mechanical vibrations as subject can be found within many Engineering and Science Degrees. To achieve that the students understand the mathematics and its physical interpretation is the objective we should get as docents. In this paper we describe how to create a simple graphical model of a single degree of freedom vibrating system allowing us to visualize concepts like above concepts damping, resonance or forced vibrations. For that, we use the popular symbolic software Wolfram Mathematica with which, without an excessive programming complexity, we can obtain a very satisfactory visual model capable to move itself, controlled by parameters. In addition, the model incorporates the curve-response, something that links the mathematical results with reality

Bayesian outcome-based strategy classification.

Hilbig and Moshagen (Psychonomic Bulletin & Review, 21, 1431-1443, 2014) recently developed a method for making inferences about the decision processes people use in multi-attribute forced choice tasks. Their paper makes a number of worthwhile theoretical and methodological contributions. Theoretically, they provide an insightful psychological motivation for a probabilistic extension of the widely-used "weighted additive" (WADD) model, and show how this model, as well as other important models like "take-the-best" (TTB), can and should be expressed in terms of meaningful priors. Methodologically, they develop an inference approach based on the Minimum Description Length (MDL) principles that balances both the goodness-of-fit and complexity of the decision models they consider. This paper aims to preserve these useful contributions, but provide a complementary Bayesian approach with some theoretical and methodological advantages. We develop a simple graphical model, implemented in JAGS, that allows for fully Bayesian inferences about which models people use to make decisions. To demonstrate the Bayesian approach, we apply it to the models and data considered by Hilbig and Moshagen (Psychonomic Bulletin & Review, 21, 1431-1443, 2014), showing how a prior predictive analysis of the models, and posterior inferences about which models people use and the parameter settings at which they use them, can contribute to our understanding of human decision making.

UN PASO MÁS ALLÁ DEL TRIÁNGULO Y EL TETRAEDRO. EL MODELO QF7 PARA EL CONOCIMIENTO DEL FUEGO

Historically, simple graphical models have been used to describe the processes of combustion and fire. The fire triangle and its variants, the fire tetrahedron and pentahedron, are some of these models. However, none of them consider characteristics such as color, smoke or flame, This short communication based on Finite Projective Geometry presents a 7 sided model called QF7, which introduces these features in the representation of the process of fire.

NATIONAL SYSTEM OF INNOVATION: A NOTE ON TECHNOLOGICAL ASYMMETRIES AND CATCHING‑UP PERSPECTIVES

What distinguishes the National Innovation System (NIS) across different countries? Could the NIS be considered a useful analytical framework to explain growth performances? Which kind of representation can supersede the "push policy view" of NIS approach? These questions are worthy of particular attention for the understanding of potential empirical and analytical achievements of this approach. This paper discusses the main approaches that explain technological divergence and convergence. It is argued that another element identified as the "national institutional dimension" has to be explicitly taken into account for the understanding of the interplay that exists between technology, specialization and growth. It also provides a macro‑representation of NIS which potentially captures and identifies at the micro, meso and macro levels the main threads that link innovation, institutions, competencies and economic performances, as well as a simple graphical model of the interplay between NIS, competencies and growth performances.