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Modeling of growing networks with directional attachment and communities.

In this paper, we propose a new network growth model and its learning algorithm to more precisely model such a real-world growing network as the Web. Unlike the conventional models, we have incorporated directional attachment and community structure for this purpose. We show that the proposed model exhibits a degree distribution with a power-law tail, which is an important characteristic of many large-scale real-world networks including the Web. Using real Web data, we experimentally show that predictive ability can be improved by incorporating directional attachment and community structure. Also, using synthetic data, we experimentally show that predictive ability can definitely be improved by incorporating community structure.

Algorithms↗

Adaptive internal state space construction method for reinforcement learning of a real-world agent.

One of the difficulties encountered in the application of the reinforcement learning to real-world problems is the construction of a discrete state space from a continuous sensory input signal. In the absence of a priori knowledge about the task, a straightforward approach to this problem is to discretize the input space into a grid, and to use a lookup table. However, this method suffers from the curse of dimensionality. Some studies use continuous function approximators such as neural networks instead of lookup tables. However, when global basis functions such as sigmoid functions are used, convergence cannot be guaranteed. To overcome this problem, we propose a method in which local basis functions are incrementally assigned depending on the task requirement. Initially, only one basis function is allocated over the entire space. The basis function is divided according to the statistical property of locally weighted temporal difference error (TD error) of the value function. We applied this method to an autonomous robot collision avoidance problem, and evaluated the validity of the algorithm in simulation. The proposed algorithm, which we call adaptive basis division (ABD) algorithm, achieved the task using a smaller number of basis functions than the conventional methods. Moreover, we applied the method to a goal-directed navigation problem of a real mobile robot. The action strategy was learned using a database of sensor data, and it was then used for navigation of a real machine. The robot reached the goal using a smaller number of internal states than with the conventional methods.

Journal Article↗

Comparative performance of species richness estimation methods.

In most real-world contexts the sampling effort needed to attain an accurate estimate of total species richness is excessive. Therefore, methods to estimate total species richness from incomplete collections need to be developed and tested. Using real and computer-simulated parasite data sets, the performances of 9 species richness estimation methods were compared. For all data sets, each estimation method was used to calculate the projected species richness at increasing levels of sampling effort. The performance of each method was evaluated by calculating the bias and precision of its estimates against the known total species richness. Performance was evaluated with increasing sampling effort and across different model communities. For the real data sets, the Chao2 and first-order jackknife estimators performed best. For the simulated data sets, the first-order jackknife estimator performed best at low sampling effort but, with increasing sampling effort, the bootstrap estimator outperformed all other estimators. Estimator performance increased with increasing species richness, aggregation level of individuals among samples and overall population size. Overall, the Chao2 and the first-order jackknife estimation methods performed best and should be used to control for the confounding effects of sampling effort in studies of parasite species richness. Potential uses of and practical problems with species richness estimation methods are discussed.

Animals↗

Assessing heart rate variability from real-world Holter reports.

Real world clinical Holter reports are often difficult to interpret from a heart rate variability (HRV) perspective. In many cases HRV software is absent. Step-by-step HRV assessment from clinical Holter reports includes: making sure that there is enough usable data, assessing maximum and minimum heart rates, assessing circadian HRV from hourly average heart rates, and assessing HRV from the histogram of R-R intervals and from the plot of R-R intervals or heart rate vs. time. If HRV data are available, time domain HRV is easiest to understand and less sensitive to scanning errors. SDNN (the standard deviation of all N-N intervals in ms) and SDANN (the standard deviation of the 5-min average of N-N intervals in ms) are easily interpreted. SDNN < 70 ms post-MI is a cut point for increased mortality risk. Two times ln SDANN is a good surrogate for ln ultra low frequency power and can be compared with published cut points. SDNNIDX (the average of the standard deviations of N-N intervals for each 5-min in ms) < 30 ms is associated with increased risk in patients with congestive heart failure. RMSSD (the root mean square of successive N-N interval difference in ms) < 17.5 ms has also been associated with increased risk post-myocardial infarction. Frequency domain HRV values are often not comparable to published data. However, graphical power spectral plots can provide additional information about whether the HRV pattern is normal and can also identify some patients with obstructive sleep apnea.

Diagnosis, Computer-Assisted↗

Distant collaboration in drug discovery: the LINK3D project.

The work describes the development of novel software supporting synchronous distant collaboration between scientists involved in drug discovery and development projects. The program allows to visualize and share data as well as to interact in real time using standard intranets and Internet resources. Direct visualization of 2D and 3D molecular structures is supported and original tools for facilitating remote discussion have been integrated. The software is multiplatform (MS-Windows, SGI-IRIX, Linux), allowing for a seamless integration of heterogeneous working environments. The project aims to support collaboration both within and between academic and industrial institutions. Since confidentiality is very important in some scenarios, special attention has been paid to security aspects. The article presents the research carried out to gather the requirements of collaborative software in the field of drug discovery and development and describes the features of the first fully functional prototype obtained. Real-world testing activities carried out on this prototype in order to guarantee its adequacy in diverse environments are also described and discussed.

Computer Graphics↗

Food-web structure and network theory: The role of connectance and size.

Networks from a wide range of physical, biological, and social systems have been recently described as "small-world" and "scale-free." However, studies disagree whether ecological networks called food webs possess the characteristic path lengths, clustering coefficients, and degree distributions required for membership in these classes of networks. Our analysis suggests that the disagreements are based on selective use of relatively few food webs, as well as analytical decisions that obscure important variability in the data. We analyze a broad range of 16 high-quality food webs, with 25-172 nodes, from a variety of aquatic and terrestrial ecosystems. Food webs generally have much higher complexity, measured as connectance (the fraction of all possible links that are realized in a network), and much smaller size than other networks studied, which have important implications for network topology. Our results resolve prior conflicts by demonstrating that although some food webs have small-world and scale-free structure, most do not if they exceed a relatively low level of connectance. Although food-web degree distributions do not display a universal functional form, observed distributions are systematically related to network connectance and size. Also, although food webs often lack small-world structure because of low clustering, we identify a continuum of real-world networks including food webs whose ratios of observed to random clustering coefficients increase as a power-law function of network size over 7 orders of magnitude. Although food webs are generally not small-world, scale-free networks, food-web topology is consistent with patterns found within those classes of networks.

Ecology↗

Determination of biokinetic interactions in chemical mixtures using real-time breath analysis and physiologically based pharmacokinetic modeling.

Regulatory agencies are challenged to conduct risk assessments on chemical mixtures without full information on toxicological interactions that may occur at real-world, low-dose exposure levels. The present study was undertaken to investigate the pharmacokinetic impact of low-dose coexposures to toluene and trichloroethylene in vivo in male F344 rats using a real-time breath analysis system coupled with physiologically based pharmacokinetic (PBPK) modeling. Rats were exposed to compounds alone or as a binary mixture, at low (5 to 25 mg/kg) or high (240 to 800 mg/kg) dose levels. Exhaled breath from the exposed animals was monitored for the parent compounds and a PBPK model was used to analyze the data. At low doses, exhaled breath kinetics from the binary mixture exposure compared with those obtained during single exposures, thus indicating that no metabolic interaction occurred with these low doses. In contract, at higher doses the binary PBPK model simulating independent metabolism was found to underpredict the exhaled breath concentration, suggesting an inhibition of metabolism. Therefore the binary mixture PBPK model was used to compare the measured exhaled breath levels from high- and low-dose exposures with the predicted levels under various metabolic interaction simulations (competitive, noncompetitive, or uncompetitive inhibition). Of these simulations, the optimized competitive metabolic interaction description yielded a Ki value closest to the Km of the inhibitor solvent, indicating that competitive inhibition is the most plausible type of metabolic interaction between these two solvents.

Anesthetics, Inhalation↗

Development of a microscale emission factor model for CO for predicting real-time motor vehicle emissions.

The U.S. Environmental Protection Agency's (EPA) National Exposure Research Laboratory has initiated a project to improve the methodology for modeling human exposure to motor vehicle emissions. The overall project goal is to develop improved methods for modeling the source through the air pathway to human exposure in significant microenvironments of exposure. This paper presents the technical description of a newly developed model for CO emissions. The sensitivity analysis and evaluation of this emission model is presented in a companion paper titled "Sensitivity Analysis and Evaluation of MicroFacCO: A Microscale Motor Vehicle Emission Factor Model for CO Emissions." The MOBILE models (used in the United States, except California) and EMFAC models (used in California only) used to estimate emissions are suitable for supporting mostly regional (county)-scale modeling and emission inventory because of their dependence on vehicle-miles-traveled aggregate data. These emission models are not designed to estimate real-time emissions needed for human exposure studies near roadways. A number of independent studies have found that current mobile source emission factor models are not very reliable at estimating microscale emissions and are, therefore, inappropriate for use with microscale modeling necessary to estimate human exposures near roadways. A microscale emission factor model for predicting real-world real-time motor vehicle CO emissions (MicroFacCO) has been developed. It uses available information on the vehicle fleet composition. The algorithm used to calculate emission factors in MicroFacCO is disaggregated based on the on-road vehicle fleet. The emission factors are calculated from a real-time fleet rather than from a fleet-wide average estimated by a vehicle-miles-traveled weighting of the emission factors for different vehicle classes. MicroFacCO uses the same database used to develop the MOBILE6 model. As compared with MOBILE emission models, MicroFacCO requires only a few input variables, which are necessary to characterize the real-time fleet being modeled. The main input variables required are on-road vehicle fleet, time and day of year, ambient temperature, and relative humidity.

Carbon Monoxide↗

Real-world cognitive--and metacognitive--dysfunction in schizophrenia: a new approach for measuring (and remediating) more "right stuff".

While the role of impaired cognition in accounting for functional outcome in schizophrenia is generally established by now, the overlap is far from complete. Moreover, little is known about the potential mechanisms that bridge between cognition and functional outcome. The aim of this article is to aid in closing this gap by presenting a novel, more ecologically valid approach for neuropsychological assessment. The new approach is motivated by the view that metacognitive processes of self-monitoring and self-regulation are fundamental determinants of competent functioning in the real world. The new approach incorporates experimental psychological concepts and paradigms used to study metacognition into current standard neuropsychological assessment procedures. Preliminary empirical data that support and demonstrate the utility of the new approach for assessment, as well as remediation efforts, in schizophrenia are presented and discussed.

Cognition Disorders↗

Restoring warped document images through 3D shape modeling.

Scanning a document page from a thick bound volume often results in two kinds of distortions in the scanned image, i.e., shade along the "spine" of the book and warping in the shade area. In this paper, we propose an efficient restoration method based on the discovery of the 3D shape of a book surface from the shading information in a scanned document image. From a technical point of view, this shape from shading (SFS) problem in real-world environments is characterized by 1) a proximal and moving light source, 2) Lambertian reflection, 3) nonuniform albedo distribution, and 4) document skew. Taking all these factors into account, we first build practical models (consisting of a 3D geometric model and a 3D optical model) for the practical scanning conditions to reconstruct the 3D shape of the book surface. We next restore the scanned document image using this shape based on deshading and dewarping models. Finally, we evaluate the restoration results by comparing our estimated surface shape with the real shape as well as the OCR performance on original and restored document images. The results show that the geometric and photometric distortions are mostly removed and the OCR results are improved markedly.

Algorithms↗

How fantasy benefits young children's understanding of pretense.

Sobel and Lillard (2001) demonstrated that 4-year-olds' understanding of the role that the mind plays in pretending improved when children were asked questions in a fantasy context. The present study investigated whether this fantasy effect was motivated by children recognizing that fantasy contains violations of real-world causal structure. In Experiment 1, 4-year-olds were shown a fantasy character engaged in ordinary actions or actions that violated causal knowledge. Children were more likely to say that a troll doll who was acting like but ignorant of the character was not pretending to be that character when read the violation story. Experiment 2 suggested that this difference was not caused by a greater interest in the violation story. Experiment 3 demonstrated a similar difference for characters engaged in social and functional violations that were possible in the real world. These data are consistent with the hypothesis that preschoolers use actions and appearance more than mental states to make judgments about pretense, but that those judgments can be influenced by the context in which the questions are presented.

Awareness↗

Predictive modeling of the shelf life of fish under nonisothermal conditions.

The behavior of the natural microflora of Mediterannean gilt-head seabream (Sparus aurata) was monitored during aerobic storage at different isothermal conditions from 0 to 15 degrees C. The growth data of pseudomonads, established as the specific spoilage organisms of aerobically stored gilt-head seabream, combined with data from previously published experiments, were used to model the effect of temperature on pseudomonad growth using a Belehradek type model. The nominal minimum temperature parameters of the Belehradek model (T(min)) for the maximum specific growth rate (micro(max)) and the lag phase (t(Lag)) were determined to be -11.8 and -12.8 degrees C, respectively. The applicability of the model in predicting pseudomonad growth on fish at fluctuating temperatures was evaluated by comparing predictions with observed growth in experiments under dynamic conditions. Temperature scenarios designed in the laboratory and simulation of real temperature profiles observed in the fish chill chain were used. Bias and accuracy factors were used as comparison indices and ranged from 0.91 to 1.17 and from 1.11 to 1.17, respectively. The average percent difference between shelf life predicted based on pseudomonad growth and shelf life experimentally determined by sensory analysis for all temperature profiles tested was 5.8%, indicating that the model is able to predict accurately fish quality in real-world conditions.

Aerobiosis↗

For real! XCS with continuous-valued inputs.

Many real-world problems are not conveniently expressed using the ternary representation typically used by Learning Classifier Systems and for such problems an interval-based representation is preferable. We analyse two interval-based representations recently proposed for XCS, together with their associated operators and find evidence of considerable representational and operator bias. We propose a new interval-based representation that is more straightforward than the previous ones and analyse its bias. The representations presented and their analysis are also applicable to other Learning Classifier System architectures. We discuss limitations of the real multiplexer problem, a benchmark problem used for Learning Classifier Systems that have a continuous-valued representation, and propose a new test problem, the checkerboard problem, that matches many classes of real-world problem more closely than the real multiplexer. Representations and operators are compared using both the real multiplexer and checkerboard problems and we find that representational, operator and sampling bias all affect the performance of XCS in continuous-valued environments.

Classification↗

Social categorizations, social comparisons and stigma: presentations of self in people with learning difficulties.

Self-categorization theory stresses the importance of the context in which the meta-contrast principle is proposed to operate. This study is concerned with how 'the pool of psychologically relevant stimuli' (Turner, Hogg, Oakes, Reicher & Wetherell, 1987, p. 47) comprising the context is determined. Data from interviews with 33 people with learning difficulties were used to show how a positive sense of self might be constructed by members of a stigmatized social category through the social worlds that they describe, and therefore the social comparisons and categorizations that are made possible. Participants made downward comparisons which focused on people with learning difficulties who were less able or who displayed challenging behaviour, and with people who did not have learning difficulties but who, according to the participants, behaved badly, such as beggars, drunks and thieves. By selection of dimensions and comparison others, a positive sense of self and a particular set of social categorizations were presented. It is suggested that when using self-categorization theory to study real-world social categories, more attention needs to be paid to the involvement of the perceiver in determining which stimuli are psychologically relevant since this is a crucial determinant of category salience.

Adolescent↗

Safety and usage pattern of low-dose diclofenac when used as an over-the-counter medication: results of an observational cohort study in a community-based pharmacy setting.

OBJECTIVE: The widespread and unsupervised nature of nonprescription drug usage makes it important that evidence of effectiveness and safety should be gathered in a real-world, over-the-counter (OTC) setting. This study was designed to evaluate the "real life" behavior of consumers with nonprescription access to low-dose diclofenac-K, with special focus on tolerability and the pattern of product usage. PARTICIPANTS AND METHODS: Participants were recruited from consumers presenting at 62 community-based pharmacies in Norway after they had purchased low-dose diclofenac-K. Baseline data were collected from the participants in the pharmacy and information on diclofenac usage, the condition for which it was used, comprehensibility of the package insert, efficacy and safety were collected 5 days after commencing the medication. Follow-up safety data were collected 19 days after commencing study medication. RESULTS: 446 individuals participated in the study with 383 taking medication and completing questionnaires at each time point. The directions for use were followed well with regard to recommended indications, contraindications and maximum dosages, but less well with respect to the recommended duration of use and concurrent medications. Most participants reported complete relief, a lot of relief, fair relief or some relief from the symptoms from which they were suffering and 70% were willing to purchase diclofenac-K again. Only 6.5% of participants reported adverse events and 6 participants (1.6%) were considered to have experienced a drug-related adverse event, none of which was considered to be severe. CONCLUSIONS: Overall, this study showed that low-dose diclofenac-K is efficacious, safe and commonly used in accordance with the directions for use when used as an OTC medication. It also demonstrated that the use of an OTC analgesic medication can be successfully monitored in a pharmacy-based cohort study.

Cohort Studies↗

A volumetric approach to virtual simulation of functional endoscopic sinus surgery.

Advanced display technologies have made the virtual exploration of relatively complex models feasible in many applications. Unfortunately, only a few human interfaces allow natural interaction with the environment. Moreover, in surgical applications, such realistic interaction requires real-time rendering of volumetric data-placing an overwhelming performance burden on the system. We report on a collaboration of an interdisciplinary group developing a virtual reality system that provides intuitive interaction with volume data by employing real-time volume rendering and force feedback (haptic) sensations. We describe our rendering methods and the haptic devices and explain its utility of this system in the real-world application of Endoscopic Sinus Surgery (ESS) simulation.

Computer Simulation↗

Intelligent aids for parallel experiment planning and macromolecular crystallization.

This paper presents a framework called Parallel Experiment Planning (PEP) that is based on an abstraction of how experiments are performed in the domain of macromolecular crystallization. The goal in this domain is to obtain a good quality crystal of a protein or other macromolecule that can be X-ray diffracted to determine three-dimensional structure. This domain presents problems encountered in real-world situations, such as a parallel and dynamic environment, insufficient resources and expensive tasks. The PEP framework comprises of two types of components: (1) an information management system for keeping track of sets of experiments, resources and costs; and (2) knowledge-based methods for providing intelligent assistance to decision-making. The significance of the developed PEP framework is three-fold--(a) the framework can be used for PEP even without one of its major intelligent aids that simulates experiments, simply by collecting real experimental data; (b) the framework with a simulator can provide intelligent assistance for experiment design by utilizing existing domain theories; and (c) the framework can help provide strategic assessment of different types of parallel experimentation plans that involve different tradeoffs.

Animals↗

Drug-eluting stents.

Drug-eluting stents represent the third revolution in the field of Interventional Cardiology following balloon angioplasty (PTCA) and the implantation of metal stents. The main limitation of percutaneous coronary intervention (PCI) is restenosis. The introduction of drug eluting stents able to release antiproliferative compounds led to the evaluation of several antiproliferative drugs in order to reduce restenosis. Rapamycin (Sirolimus) has been demonstrated to inhibit smooth muscle cell (SMC) proliferation and migration in vitro and to reduce in vivo neointima formation with blockage of the cell cycle progression at the G1-S transition. In a pilot study, recently confirmed by a randomized trial, rapamycin drug-eluting stents have been reported to eliminate restenosis after stent implantation. Promising data also come from the use of paclitaxel drug-eluting stents. Paclitaxel (Taxol) is a microtubule-stabilizing agent with potent antiproliferative activity. Even if drug-eluting stents represent one of the most promising fields in Interventional Cardiology today before being sure of their real potential it is necessary to wait for results from several ongoing clinical studies, their usage in real-world lesions and extended follow-up to 5 years.

Angioplasty, Balloon, Coronary↗