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Several variable selection algorithms in multivariate calibration can be accelerated using Graphics Processing Units (GPU). Among these algorithms, the Firefly Algorithm (FA) is a recent proposed metaheuristic that may be used for variable selection. This paper presents a GPU-based FA (FA-MLR) with multiobjective formulation for variable selection in multivariate calibration problems and compares it with some traditional sequential algorithms in the literature. The advantage of the proposed implementation is demonstrated in an example involving a relatively large number of variables. The results showed that the FA-MLR, in comparison with the traditional algorithms is a more suitable choice and a relevant contribution for the variable selection problem. Additionally, the results also demonstrated that the FA-MLR performed in a GPU can be five times faster than its sequential implementation. [ABSTRACT FROM AUTHOR]

The spinocerebellar systems are essential for the brain in the performance of coordinated movements, but our knowledge about the spinocerebellar interactions is very limited. Recently, several crucial pieces of information have been acquired for the spinal border cell (SBC) component of the ventral spinocerebellar tract (VSCT), as well as the effects of SBC mossy fiber activation in granule cells of the cerebellar cortex. SBCs receive monosynaptic input from the reticulospinal tract (RST), which is an important driving system under locomotion, and disynaptic inhibition from Ib muscle afferents. The patterns of activity of RST neurons and Ib afferents under locomotion are known. The activity of VSCT neurons under fictive locomotion, i.e. without sensory feedback, is also known, but there is little information on how these neurons behave under actual locomotion and for cerebellar granule cells receiving SBC input this is completely unknown. But the available information makes it possible to simulate the interactions between the spinal and cerebellar neuronal circuitries with a relatively large set of biological constraints. Using a model of the various neuronal elements and the network they compose, we simulated the modulation of the SBCs and their target granule cells under locomotion and hence generated testable predictions of their general pattern of modulation under this condition. This particular system offers a unique opportunity to simulate these interactions with a limited number of assumptions, which helps making the model biologically plausible. Similar principles of information processing may be expected to apply to all spinocerebellar systems. [ABSTRACT FROM AUTHOR]

We study cyclic evolutionary games in a spatial diluted grid environment in which agents strategically interact locally but can also opportunistically move to other positions within a given migration radius. We find that opportunistic migration can inverse the cyclic prevalence between the strategies when the frequency of random imitation is large enough compared to the payoff-driven imitation. At the transition the average size of the patterns diverges and this threatens diversity of strategies. [ABSTRACT FROM AUTHOR]

Background: Measurement of camouflage performance is of fundamental importance for military stealth applications. The goal of camouflage assessment algorithms is to automatically assess the effect of camouflage in agreement with human detection responses. In a previous study, we found that the Universal Image Quality Index (UIQI) correlated well with the psychophysical measures, and it could be a potentially camouflage assessment tool. Methodology: In this study, we want to quantify the camouflage similarity index and psychophysical results. We compare several image quality indexes for computational evaluation of camouflage effectiveness, and present the results of an extensive human visual experiment conducted to evaluate the performance of several camouflage assessment algorithms and analyze the strengths and weaknesses of these algorithms. Significance: The experimental data demonstrates the effectiveness of the approach, and the correlation coefficient result of the UIQI was higher than those of other methods. This approach was highly correlated with the human target-searching results. It also showed that this method is an objective and effective camouflage performance evaluation method because it considers the human visual system and image structure, which makes it consistent with the subjective evaluation results. [ABSTRACT FROM AUTHOR]

Adjuvant therapy of stage IIB/III melanoma with interferon reduces relapse and mortality by up to 33% but is accompanied by toxicity-related complications. Polymorphisms of the CTLA-4 gene associated with autoimmune diseases could help in identifying interferon treatment benefits. We previously genotyped 286 melanoma patients and 288 healthy (unrelated) individuals for six CTLA-4 polymorphisms (SNP). Previous analyses found no significant differences between the distributions of CTLA-4 polymorphisms in the melanoma population vs. controls, no significant difference in relapse free and overall survivals among patients and no correlation between autoimmunity and specific alleles. We report new analysis of these CTLA-4 genetic profiles, using Network Phenotyping Strategy (NPS). It is graph-theory based method, analyzing the SNP patterns. Application of NPS on CTLA-4 polymorphism captures allele relationship pattern for every patient into 6-partite mathematical graph P. Graphs P are combined into weighted 6-partite graph S, which subsequently decomposed into reference relationship profiles (RRP). Finally, every individual CTLA-4 genotype pattern is characterized by the graph distances of P from eight identified RRP's. RRP's are subgraphs of S, collecting equally frequent binary allele co-occurrences in all studied loci. If S topology represents the genetic “dominant model”, the RRP's and their characteristic frequencies are identical to expectation-maximization derived haplotypes and maximal likelihood estimates of their frequencies. The graph-representation allows showing that patient CTLA-4 haplotypes are uniquely different from the controls by absence of specific SNP combinations. New function-related insight is derived when the 6-partite graph reflects allelic state of CTLA-4. We found that we can use differences between individual P and specific RRPs to identify patient subpopulations with clearly different polymorphic patterns relatively to controls as well as to identify patients with significantly different survival. [ABSTRACT FROM AUTHOR]

We describe a supervised prediction method for diagnosis of acute myeloid leukemia (AML) from patient samples based on flow cytometry measurements. We use a data driven approach with machine learning methods to train a computational model that takes in flow cytometry measurements from a single patient and gives a confidence score of the patient being AML-positive. Our solution is based on an regularized logistic regression model that aggregates AML test statistics calculated from individual test tubes with different cell populations and fluorescent markers. The model construction is entirely data driven and no prior biological knowledge is used. The described solution scored a 100% classification accuracy in the DREAM6/FlowCAP2 Molecular Classification of Acute Myeloid Leukaemia Challenge against a golden standard consisting of 20 AML-positive and 160 healthy patients. Here we perform a more extensive validation of the prediction model performance and further improve and simplify our original method showing that statistically equal results can be obtained by using simple average marker intensities as features in the logistic regression model. In addition to the logistic regression based model, we also present other classification models and compare their performance quantitatively. The key benefit in our prediction method compared to other solutions with similar performance is that our model only uses a small fraction of the flow cytometry measurements making our solution highly economical. [ABSTRACT FROM AUTHOR]

This paper investigates the steady hydromagnetic three-dimensional boundary layer flow of Maxwell fluid over a bidirectional stretching surface. Both cases of prescribed surface temperature (PST) and prescribed surface heat flux (PHF) are considered. Computations are made for the velocities and temperatures. Results are plotted and analyzed for PST and PHF cases. Convergence analysis is presented for the velocities and temperatures. Comparison of PST and PHF cases is given and examined. [ABSTRACT FROM AUTHOR]

In this paper, I investigate the co-evolution of fast and slow strategy spread and game strategies in populations of spatially distributed agents engaged in a one off evolutionary dilemma game. Agents are characterized by a pair of traits, a game strategy (cooperate or defect) and a binary ‘advertising’ strategy (advertise or don’t advertise). Advertising, which comes at a cost , allows investment into faster propagation of the agents’ traits to adjacent individuals. Importantly, game strategy and advertising strategy are subject to the same evolutionary mechanism. Via analytical reasoning and numerical simulations I demonstrate that a range of advertising costs exists, such that the prevalence of cooperation is significantly enhanced through co-evolution. Linking costly replication to the success of cooperators exposes a novel co-evolutionary mechanism that might contribute towards a better understanding of the origins of cooperation-supporting heterogeneity in agent populations. [ABSTRACT FROM AUTHOR]

: The brain is able to maintain a stable perception although the visual stimuli vary substantially on the retina due to geometric transformations and lighting variations in the environment. This paper presents a theory for achieving basic invariance properties already at the level of receptive fields. Specifically, the presented framework comprises (i) local scaling transformations caused by objects of different size and at different distances to the observer, (ii) locally linearized image deformations caused by variations in the viewing direction in relation to the object, (iii) locally linearized relative motions between the object and the observer and (iv) local multiplicative intensity transformations caused by illumination variations. The receptive field model can be derived by necessity from symmetry properties of the environment and leads to predictions about receptive field profiles in good agreement with receptive field profiles measured by cell recordings in mammalian vision. Indeed, the receptive field profiles in the retina, LGN and V1 are close to ideal to what is motivated by the idealized requirements. By complementing receptive field measurements with selection mechanisms over the parameters in the receptive field families, it is shown how true invariance of receptive field responses can be obtained under scaling transformations, affine transformations and Galilean transformations. Thereby, the framework provides a mathematically well-founded and biologically plausible model for how basic invariance properties can be achieved already at the level of receptive fields and support invariant recognition of objects and events under variations in viewpoint, retinal size, object motion and illumination. The theory can explain the different shapes of receptive field profiles found in biological vision, which are tuned to different sizes and orientations in the image domain as well as to different image velocities in space-time, from a requirement that the visual system should be invariant to the natural types of image transformations that occur in its environment. [ABSTRACT FROM AUTHOR]

Subcellular localization of a protein is important to understand proteins’ functions and interactions. There are many techniques based on computational methods to predict protein subcellular locations, but it has been shown that many prediction tasks have a training data shortage problem. This paper introduces a new method to mine proteins with non-experimental annotations, which are labeled by non-experimental evidences of protein databases to overcome the training data shortage problem. A novel active sample selection strategy is designed, taking advantage of active learning technology, to actively find useful samples from the entire data pool of candidate proteins with non-experimental annotations. This approach can adequately estimate the “value” of each sample, automatically select the most valuable samples and add them into the original training set, to help to retrain the classifiers. Numerical experiments with for four popular multi-label classifiers on three benchmark datasets show that the proposed method can effectively select the valuable samples to supplement the original training set and significantly improve the performances of predicting classifiers. [ABSTRACT FROM AUTHOR]

How to identify influential nodes is a key issue in complex networks. The degree centrality is simple, but is incapable to reflect the global characteristics of networks. Betweenness centrality and closeness centrality do not consider the location of nodes in the networks, and semi-local centrality, leaderRank and pageRank approaches can be only applied in unweighted networks. In this paper, a bio-inspired centrality measure model is proposed, which combines the Physarum centrality with the K-shell index obtained by K-shell decomposition analysis, to identify influential nodes in weighted networks. Then, we use the Susceptible-Infected (SI) model to evaluate the performance. Examples and applications are given to demonstrate the adaptivity and efficiency of the proposed method. In addition, the results are compared with existing methods. [ABSTRACT FROM AUTHOR]

Regulatory networks play a central role in cellular behavior and decision making. Learning these regulatory networks is a major task in biology, and devising computational methods and mathematical models for this task is a major endeavor in bioinformatics. Boolean networks have been used extensively for modeling regulatory networks. In this model, the state of each gene can be either ‘on’ or ‘off’ and that next-state of a gene is updated, synchronously or asynchronously, according to a Boolean rule that is applied to the current-state of the entire system. Inferring a Boolean network from a set of experimental data entails two main steps: first, the experimental time-series data are discretized into Boolean trajectories, and then, a Boolean network is learned from these Boolean trajectories. In this paper, we consider three methods for data discretization, including a new one we propose, and three methods for learning Boolean networks, and study the performance of all possible nine combinations on four regulatory systems of varying dynamics complexities. We find that employing the right combination of methods for data discretization and network learning results in Boolean networks that capture the dynamics well and provide predictive power. Our findings are in contrast to a recent survey that placed Boolean networks on the low end of the “faithfulness to biological reality” and “ability to model dynamics” spectra. Further, contrary to the common argument in favor of Boolean networks, we find that a relatively large number of time points in the time-series data is required to learn good Boolean networks for certain data sets. Last but not least, while methods have been proposed for inferring Boolean networks, as discussed above, missing still are publicly available implementations thereof. Here, we make our implementation of the methods available publicly in open source at http://bioinfo.cs.rice.edu/. [ABSTRACT FROM AUTHOR]

M/G/C/C state dependent queuing networks consider service rates as a function of the number of residing entities (e.g., pedestrians, vehicles, and products). However, modeling such dynamic rates is not supported in modern Discrete Simulation System (DES) software. We designed an approach to cater this limitation and used it to construct the M/G/C/C state-dependent queuing model in Arena software. Using the model, we have evaluated and analyzed the impacts of various arrival rates to the throughput, the blocking probability, the expected service time and the expected number of entities in a complex network topology. Results indicated that there is a range of arrival rates for each network where the simulation results fluctuate drastically across replications and this causes the simulation results and analytical results exhibit discrepancies. Detail results that show how tally the simulation results and the analytical results in both abstract and graphical forms and some scientific justifications for these have been documented and discussed. [ABSTRACT FROM AUTHOR]

Risk management is a problem humans have faced throughout history and across societies. One way to manage risk is to transfer it to other parties through formal and informal insurance systems. One informal method of self-insurance is limited risk pooling, where individuals can ask for help only when in need. Models suggest that need-based transfer systems may require coordination and common knowledge to be effective. To explore the impact of common knowledge on social coordination and risk pooling in volatile environments, we designed and ran a Risk Pooling Game. We compared participants who played the game with no advance priming or framing to participants who read one of two texts describing real-world systems of risk pooling. Players in the primed games engaged in more repetitive asking and repetitive giving than those in the control games. Players in the primed games also gave more in response to requests and were more likely to respond positively to requests than players in the control games. In addition, players in the primed games were more tolerant of wide differences between what the two players gave and received. These results suggest that the priming texts led players to pay less attention to debt and repayment and more attention to the survival of the other player, and thus to more risk pooling. These results are consistent with findings from fieldwork in small-scale societies that suggest that humans use need-based transfer systems to pool risk when environmental volatility leads to needs with unpredictable timing. Models suggest that the need-based transfer strategy observed in this experiment can outperform debt-based strategies. The results of the present study suggest that the suite of behaviors associated with need-based transfers is an easily triggered part of the human behavioral repertoire. [ABSTRACT FROM AUTHOR]

In this study, a complexity-quality analysis with transcoding architectures is proposed for reducing inverse quantization numbers. This architecture is different from conventional transcoding scheme, which neglects the relationship between previous and current quantizer step size. However, the proposed transcoding architecture depends on the modulus of the ratio of the current and previous quantization parameter. By analyzing the quantized area of the previous and current quantization parameter, we concluded the part of undoing first inverse quantization, to reduce computing complexity. From computer simulation, we verify the merits of the proposed scheme over the conventional transcoding approaches, in terms of achieving better performance based on the computing complexity and objective (e.g., the peak signal-to-noise ratio) analysis. [ABSTRACT FROM AUTHOR]

Most people have a desire to live in a just world, a place where good things happen to good people and bad things happen to bad people. And yet, injustices do occur: good things happen to bad people and bad things happen to good people. Across four experiments, we show that people respond quite differently to correct these two types of injustices. When bad things happen to good people, individuals are eager to compensate a good person’s losses, but only do so to a small degree. In contrast, when a good thing happens to a bad person, because the only perceived appropriate act of punishment is to fully strip the bad actor of all his or her illegitimate gains, few people choose to punish in this costly way. However, when they do, they do so to very large degrees. Moreover, we demonstrate that differential psychological mechanisms drive this asymmetry. [ABSTRACT FROM AUTHOR]

In this work, we investigate properties of bidirectional pedestrian streams by studying different experimental datasets from multiple authors. Through the comparison of a scenario where lanes naturally form with two others where lane formation is either obstructed or facilitated, we show the relationship of different pedestrian quantities in regard to the flow ratio (or directional split). On this scope, two measures to account for the degree of congestion and self-organization are introduced. The analysis of the results reveals that the balanced case (where flow is almost equal in both directions) has very peculiar properties which depends on the existence or not of organized lanes and their stability. While the balanced case generally shows the highest level of congestion, this property can quickly change after lanes are formed and when they remain stable. An in-depth investigation revealed that capacity in bidirectional streams is characterized by a dual nature: conflicts with the counter flow and self-organization in lanes. Both aspects have been described using a mathematical model which allowed to define a function for capacity in relation with flow ratio and environmental/cognitive aspects. The expression for capacity proposed in our work agrees with several studies from the literature, eventually allowing to understand the differences among them. We believe our function for capacity enables a more universal treatment of bidirectional streams compared to previous definitions, since it allows to account for steady and non-steady state conditions which represent important mechanisms in their dynamics. The framework introduced here may also help measuring the influence of environmental/cognitive changes in relation with the capacity of bidirectional pedestrian streams. [ABSTRACT FROM AUTHOR]

When estimating psychometric functions with sampling procedures, psychophysical assessments should be precise and accurate while being as efficient as possible to reduce assessment duration. The estimation performance of sampling procedures is commonly evaluated in computer simulations for single psychometric functions and reported using metrics as a function of number of trials. However, the estimation performance of a sampling procedure may vary for different psychometric functions. Therefore, the results of these type of evaluations may not be generalizable to a heterogeneous population of interest. In addition, the maximum number of trials is often imposed by time restrictions, especially in clinical applications, making trial-based metrics suboptimal. Hence, the benefit of these simulations to select and tune an ideal sampling procedure for a specific application is limited. We suggest to evaluate the estimation performance of sampling procedures in simulations covering the entire range of psychometric functions found in a population of interest, and propose a comprehensive set of performance metrics for a detailed analysis. To illustrate the information gained from these metrics in an application example, six sampling procedures were evaluated in a computer simulation based on prior knowledge on the population distribution and requirements from proprioceptive assessments. The metrics revealed limitations of the sampling procedures, such as inhomogeneous or systematically decreasing performance depending on the psychometric functions, which can inform the tuning process of a sampling procedure. More advanced metrics allowed directly comparing overall performances of different sampling procedures and select the best-suited sampling procedure for the example application. The proposed analysis metrics can be used for any sampling procedure and the estimation of any parameter of a psychometric function, independent of the shape of the psychometric function and of how such a parameter was estimated. This framework should help to accelerate the development process of psychophysical assessments. [ABSTRACT FROM AUTHOR]

We investigate the effectiveness of using the Rosenbrock method for numerical solution of 1D nonlinear Schrödinger equation (or the set of equations) with artificial boundary conditions (ABCs). We compare the computer simulation results obtained during long time interval at using the finite-difference scheme based on the Rosenbrock method and at using the conservative finite-difference scheme. We show, that the finite-difference scheme based on the Rosenbrock method is conditionally conservative one. To combine the advantages of both numerical methods, we propose new implicit and conditionally conservative combined method based on using both the conservative finite-difference scheme and conditionally conservative Rosenbrock method and investigate its effectiveness. The combined method allows decreasing the computer simulation time in comparison with the corresponding computer simulation time at using the Rosenbrock method. In practice, the combined method is effective at computation during short time interval, which does not require an asymptotic stability property for the finite-difference scheme. We generalize also the combined method with ABCs for 2D case. [ABSTRACT FROM AUTHOR]

Cardiac electrophysiological simulations are computationally intensive tasks. The growing complexity of cardiac models, together with the increasing use of large ensembles of models (known as populations of models), make extensive simulation studies unfeasible for regular stand-alone computers. To address this problem, we developed DENIS, a cardiac electrophysiology simulator based on the volunteer computing paradigm. We evaluated the performance of DENIS by testing the effect of simulation length, task deadline, and batch size, on the time to complete a batch of simulations. In the experiments, the time to complete a batch of simulations did not increase with simulation length, and had little dependence on batch size. In a test case involving the generation of a population of models, DENIS was able to reduce the simulation time from years to a few days when compared to a stand-alone computer. Such capacity makes it possible to undertake large cardiac simulation projects without the need for high performance computing infrastructure. [ABSTRACT FROM AUTHOR]

While having high bandwidth-efficiency, the ad-hoc on-demand distance vector (AODV) routing protocol suffers from high signaling overhead due to route request (RREQ) messages flooding, especially when the node density and the number of connections are increased. In order to resolve this broadcast storm problem of the AODV in a high node density mobile ad-hoc network, we propose a geographical on-demand route discovery scheme. Assuming a known location of the destination, the RREQ of the proposed routing protocol is propagated in a unicast manner by employing a novel parsing mechanism for possible duplicate RREQs. The routing overhead of the proposed routing protocol is greatly robust to the node density change. We derive the node density required for the proposed routing protocol to keep the same connectivity as the AODV under the circumstance where the nodes are uniformly distributed. In addition, we present an imaginary destination consideration method to incorporate the uncertainty of the destination’s location due to mobility. Computer simulations show that the proposed scheme enables the RREQ propagation to cover 95% of the one-hop communication area centered at the originally known location of the destination without sacrificing the unicast feature. [ABSTRACT FROM AUTHOR]

Objectives: To investigate changes in children’s television and computer time according to three socio-economic status (SES) indicators. Design: Prospective cohort study. Methods: Data were drawn from the European Youth Heart Study and included longitudinal data collected in 1997 and 2003 in Denmark. Television and computer time were self-reported by children. Parental education, income and ethnicity were parent-reported. Baseline data were available for 549 children (47.0% boys, 9.6 years). Generalized linear mixed models analyzed whether changes in television and computer time from baseline to follow-up differed according to the SES-indicators. Result: TV viewing time increased with 25% over time (ExpB = 1.25, 95% CI = 1.04–1.50). At both time points, children with two higher educated parents viewed 25% less hours of television than children with no higher educated parents (ExpB = 0.75, 95% CI = 0.60–0.94) and one higher educated parent (ExpB = 0.75, 95%CI = 0.59–0.97). Among children with no higher educated parents the odds of being in a higher category of computer time increased with 80% over time (OR = 1.80, 95% CI = 1.24–2.60). Among children with two higher educated parents the odds of being in a higher category of computer time decreased with 45% over time (OR = 0.55, 95% CI = 0.32–0.94). The association with ethnicity showed that white children had 42% lower odds (OR = 0.58; 95% CI = 0.34–1.00) of being in a higher category of computer time than non-white children. No significant associations were found for parental income. Conclusions: The most important SES measure of screen-based behaviors in children was parental education. Ethnicity was only associated with computer time. Financial resources were less relevant for changes in television viewing and computer use. [ABSTRACT FROM AUTHOR]

On the basis of the Crank-Nicolson method, we develop a conservative finite-difference scheme for investigation of the THz pulse interaction with a multilevel medium, covered by a disordered layered structure, in the framework of the Maxwell-Bloch equations, describing the substance evolution and the electromagnetic field evolution. For this set of the partial differential equations, the conservation laws are derived and proved. We generalize the Bloch invariant with respect to the multilevel medium. The approximation order of the developed finite-difference scheme is investigated and its conservatism property is also proved. To solve the difference equations, which are nonlinear with respect to the electric field strength, we propose an iteration method and its convergence is proved. To increase the computer simulation efficiency, we use the well-known solution of Maxwell’s equations in 1D case as artificial boundary condition. It is approximated using Cabaret scheme with the second order of an accuracy. On the basis of developed finite-difference scheme, we investigate the broadband THz pulse interaction with a medium covered by a disordered structure. This problem is of interest for the substance detection and identification. We show that the disordered structure dramatically induces an appearance of the substance false absorption frequencies. We demonstrate also that the spectrum for the transmitted and reflected pulses becomes broader due to the cascade mechanism of the high energy levels excitation of molecules. It leads to the substance emission at the frequencies, which are far from the frequency range for the incident pulse spectrum. Time-dependent spectral intensities at these frequencies are weakly disturbed by the disordered cover and, hence, they can be used for the substance identification. [ABSTRACT FROM AUTHOR]

The relation of the individual speech-in-noise performance differences in cochlear implant (CI) users to underlying physiological factors is currently poorly understood. This study approached this research question by a step-wise individualization of a computer model of speech intelligibility mimicking the details of CI signal processing and some details of the physiology present in CI users. Two factors, the electrical field spatial spread and internal noise (as a coarse model of the individual cognitive performance) were incorporated. Internal representations of speech-in-noise mixtures calculated by the model were classified using an automatic speech recognizer backend employing Hidden Markov Models with a Gaussian probability distribution. One-dimensional electric field spatial spread functions were inferred from electrical field imaging data of 14 CI users. Simplified assumptions of homogenously distributed auditory nerve fibers along the cochlear array and equal distance between electrode array and nerve tissue were assumed in the model. Internal noise, whose standard deviation was adjusted based on either anamnesis data, or text-reception-threshold data, or a combination thereof, was applied to the internal representations before classification. A systematic model evaluation showed that predicted speech-reception-thresholds (SRTs) in stationary noise improved (decreased) with decreasing internal noise standard deviation and with narrower electric field spatial spreads. The model version that was individualized to actual listeners using internal noise alone (containing average spatial spread) showed significant correlations to measured SRTs, reflecting the high correlation of the text-reception threshold data with SRTs. However, neither individualization to spatial spread functions alone, nor a combined individualization based on spatial spread functions and internal noise standard deviation did produce significant correlations with measured SRTs. [ABSTRACT FROM AUTHOR]

Many studies that aim to detect model-free and model-based influences on behavior employ two-stage behavioral tasks of the type pioneered by Daw and colleagues in 2011. Such studies commonly modify existing two-stage decision paradigms in order to better address a given hypothesis, which is an important means of scientific progress. It is, however, critical to fully appreciate the impact of any modified or novel experimental design features on the expected results. Here, we use two concrete examples to demonstrate that relatively small changes in the two-stage task design can substantially change the pattern of actions taken by model-free and model-based agents as a function of the reward outcomes and transitions on previous trials. In the first, we show that, under specific conditions, purely model-free agents will produce the reward by transition interactions typically thought to characterize model-based behavior on a two-stage task. The second example shows that model-based agents’ behavior is driven by a main effect of transition-type in addition to the canonical reward by transition interaction whenever the reward probabilities of the final states do not sum to one. Together, these examples emphasize the task-dependence of model-free and model-based behavior and highlight the benefits of using computer simulations to determine what pattern of results to expect from both model-free and model-based agents performing a given two-stage decision task in order to design choice paradigms and analysis strategies best suited to the current question. [ABSTRACT FROM AUTHOR]

In order to test the feasibility of computer simulation in field maize planting, the selection of the method of single seed precise sowing in maize is studied based on the quadratic function model Y = A×(D-Dm)2+Ym, which depicts the relationship between maize yield and planting density. And the advantages and disadvantages of the two planting methods under the condition of single seed sowing are also compared: Method 1 is optimum density planting, while Method 2 is the ideal seedling emergence number planting. It is found that the yield reduction rate and yield fluctuation of Method 2 are all lower than those of Method 1. The yield of Method 2 increased by at least 0.043 t/hm2, and showed more advantages over Method 1 with higher yield level. Further study made on the influence of seedling emergence rate on the yield of maize finds that the yields of the two methods are both highly positively correlated with the seedling emergence rate and the standard deviations of their yields are both highly negatively correlated with the seedling emergence rate. For the study of the break-up problem of sparse caused by the method of single seed precise sowing, the definition of seedling missing spots is put forward. The study found that the relationship between number of hundred-dot spot and field seedling emergence rate is as the parabola function y = -189.32x2 + 309.55x - 118.95 and the relationship between number of spot missing seedling and field seedling emergence rate is as the negative exponent function y = 395.69e-6 . 144x. The results may help to guide the maize seeds production and single seed precise sowing to some extent. [ABSTRACT FROM AUTHOR]

The equal headway instability—the fact that a configuration with regular time intervals between vehicles tends to be volatile—is a common regulation problem in public transportation systems. An unsatisfactory regulation results in low efficiency and possible collapses of the service. Computational simulations have shown that self-organizing methods can regulate the headway adaptively beyond the theoretical optimum. In this work, we develop a computer simulation for metro systems fed with real data from the Mexico City Metro to test the current regulatory method with a novel self-organizing approach. The current model considers overall system’s data such as minimum and maximum waiting times at stations, while the self-organizing method regulates the headway in a decentralized manner using local information such as the passenger’s inflow and the positions of neighboring trains. The simulation shows that the self-organizing method improves the performance over the current one as it adapts to environmental changes at the timescale they occur. The correlation between the simulation of the current model and empirical observations carried out in the Mexico City Metro provides a base to calculate the expected performance of the self-organizing method in case it is implemented in the real system. We also performed a pilot study at the Balderas station to regulate the alighting and boarding of passengers through guide signs on platforms. The analysis of empirical data shows a delay reduction of the waiting time of trains at stations. Finally, we provide recommendations to improve public transportation systems. [ABSTRACT FROM AUTHOR]

The experiments reported here used “Reversed-Interior” (RI) primes (e.g., cetupmor-COMPUTER) in three different masked priming paradigms in order to test between different models of orthographic coding/visual word recognition. The results of Experiment 1, using a standard masked priming methodology, showed no evidence of priming from RI primes, in contrast to the predictions of the Bayesian Reader and LTRS models. By contrast, Experiment 2, using a sandwich priming methodology, showed significant priming from RI primes, in contrast to the predictions of open bigram models, which predict that there should be no orthographic similarity between these primes and their targets. Similar results were obtained in Experiment 3, using a masked prime same-different task. The results of all three experiments are most consistent with the predictions derived from simulations of the Spatial-coding model. [ABSTRACT FROM AUTHOR]

Background: Tumor vasculature is critical for tumor growth, formation of distant metastases and efficiency of radio- and chemotherapy treatments. However, how the vasculature itself is affected during cancer treatment regarding to the metastatic behavior has not been thoroughly investigated. Therefore, the aim of this study was to analyze the influence of hypofractionated radiotherapy and cisplatin chemotherapy on vessel tree geometry and metastasis formation in a small cell lung cancer xenograft mouse tumor model to investigate the spread of malignant cells during different treatments modalities. Methods: The biological data gained during these experiments were fed into our previously developed computer model “Cancer and Treatment Simulation Tool” (CaTSiT) to model the growth of the primary tumor, its metastatic deposit and also the influence on different therapies. Furthermore, we performed quantitative histology analyses to verify our predictions in xenograft mouse tumor model. Results: According to the computer simulation the number of cells engrafting must vary considerably to explain the different weights of the primary tumor at the end of the experiment. Once a primary tumor is established, the fractal dimension of its vasculature correlates with the tumor size. Furthermore, the fractal dimension of the tumor vasculature changes during treatment, indicating that the therapy affects the blood vessels’ geometry. We corroborated these findings with a quantitative histological analysis showing that the blood vessel density is depleted during radiotherapy and cisplatin chemotherapy. The CaTSiT computer model reveals that chemotherapy influences the tumor’s therapeutic susceptibility and its metastatic spreading behavior. Conclusion: Using a system biological approach in combination with xenograft models and computer simulations revealed that the usage of chemotherapy and radiation therapy determines the spreading behavior by changing the blood vessel geometry of the primary tumor. [ABSTRACT FROM AUTHOR]

Objective: Letters from the hospital to the general practitioner are important for maintaining continuity of care. Although doctors feel letters are important, they are often not written on time. To improve the number and timeliness of letters sent from the hospital outpatient department to the general practitioner using an email-based intervention evaluated in a randomized controlled trial. Materials and methods: Users were interviewed to determine the requirements for the intervention. Due to high between-doctor variation at baseline, doctors were matched for baseline performance and pair-randomized. The effectiveness of the intervention was assessed using meta-analytic methods. The primary outcome was the number of patient visits which should have generated a letter that had a letter by 90 days after the visit. Satisfaction was assessed with an anonymous survey. Results: The intervention consisted of a monthly email reminder for each doctor containing a list of his or her patients who were (over)due for a letter. Doctors in the intervention group had 21% fewer patient visits which did not have a letter by 90 days (OR = 5.7, p = 0.0020). Satisfaction with the system was very high. Discussion: This study examines the effect of a simple reminder in absence of other interventions, and provides an example of an effective non-interruptive decision support intervention. Conclusion: A simple email reminder improved the number and timeliness of letters from the outpatient department to the general practitioner, and was viewed as a useful service by its users. [ABSTRACT FROM AUTHOR]

The purpose of this study was to explore the relationships among employees' usage intention pertaining to mobile information devices, focusing on subjective judgement, technology acceptance tendency, information sharing behavior and information transfer. A research model was established to verify several hypotheses. The research model based on integrated concepts of knowledge management and technology acceptance modeling. Participants were employees of enterprises in Taiwan, selected by combining snowball and convenience sampling. Data obtained from 779 e-surveys. Multiple-regression analysis was employed for hypothesis verification. The results indicate that perceived ease-of-use of mobile devices was affected by computer self-efficacy and computer playfulness directly; meanwhile, perceived ease-of-use directly affects perceived usefulness. In addition, perceived ease-of-use and perceived usefulness can predict information-sharing behavior in a positive manner, and impact knowledge transfer as well. Based on the research findings, it suggested that enterprises should utilize mobile information devices to create more contact with customers and enrich their service network. In addition, it is recommended that managers use mobile devices to transmit key information to their staff and that they use these devices for problem-solving and decision-making. Further, the staff’s skills pertaining to the operation of mobile information devices and to fully implement their features are reinforced in order to inspire the users' knowledge transfer. Enhancing the playfulness of the interface is also important. In general, it is useful to promote knowledge transfer behavior within an organization by motivating members to share information and ideas via mobile information devices. In addition, a well-designed interface can facilitate employees' use of these devices. [ABSTRACT FROM AUTHOR]

We compare three state-of-the-art Bayesian inference methods for the estimation of the unknown parameters in a stochastic model of a genetic network. In particular, we introduce a stochastic version of the paradigmatic synthetic multicellular clock model proposed by Ullner et al., 2007. By introducing dynamical noise in the model and assuming that the partial observations of the system are contaminated by additive noise, we enable a principled mechanism to represent experimental uncertainties in the synthesis of the multicellular system and pave the way for the design of probabilistic methods for the estimation of any unknowns in the model. Within this setup, we tackle the Bayesian estimation of a subset of the model parameters. Specifically, we compare three Monte Carlo based numerical methods for the approximation of the posterior probability density function of the unknown parameters given a set of partial and noisy observations of the system. The schemes we assess are the particle Metropolis-Hastings (PMH) algorithm, the nonlinear population Monte Carlo (NPMC) method and the approximate Bayesian computation sequential Monte Carlo (ABC-SMC) scheme. We present an extensive numerical simulation study, which shows that while the three techniques can effectively solve the problem there are significant differences both in estimation accuracy and computational efficiency. [ABSTRACT FROM AUTHOR]

Government initiatives have tried to ensure uniform computer access for young people; however a divide related to socioeconomic status (SES) may still exist in the nature of information technology (IT) use. This study aimed to investigate this relationship in 1,351 Western Australian children between 6 and 17 years of age. All participants had computer access at school and 98.9% at home. Neighbourhood SES was related to computer use, IT activities, playing musical instruments, and participating in vigorous physical activity. Participants from higher SES neighbourhoods were more exposed to school computers, reading, playing musical instruments, and vigorous physical activity. Participants from lower SES neighbourhoods were more exposed to TV, electronic games, mobile phones, and non-academic computer activities at home. These patterns may impact future economic, academic, and health outcomes. Better insight into neighbourhood SES influences will assist in understanding and managing the impact of computer use on young people’s health and development. [ABSTRACT FROM AUTHOR]

The idea that life may have started with an “RNA world” is attractive. Wherein, a crucial event (perhaps at the very beginning of the scenario) should have been the emergence of a ribozyme that catalyzes its own replication, i.e., an RNA replicase. Although now there is experimental evidence supporting the chemical feasibility of such a ribozyme, the evolutionary dynamics of how the replicase could overcome the “parasite” problem (because other RNAs may also exploit this ribozyme) and thrive, as described in the scenario, remains unclear. It has been suggested that spatial limitation may have been important for the replicase to confront parasites. However, more studies showed that such a mechanism is not sufficient when this ribozyme’s altruistic trait is taken into full consideration. “Tag mechanism”, which means labeling the replicase with a short subsequence for recognition in replication, may be a further mechanism supporting the thriving of the replicase. However, because parasites may also “equip” themselves with the tag, it is far from clear whether the tag mechanism could take effect. Here, we conducted a computer simulation using a Monte-Carlo model to study the evolutionary dynamics surrounding the development of a tag-driven (polymerase-type) RNA replicase in the RNA world. We concluded that (1) with the tag mechanism the replicase could resist the parasites and become prosperous, (2) the main underlying reason should be that the parasitic molecules, especially those strong parasites, are more difficult to appear in the tag-driven system, and (3) the tag mechanism has a synergic effect with the spatial limitation mechanism–while the former provides “time” for the replicase to escape from parasites, the latter provides “space” for the replicase to escape. Notably, tags may readily serve as “control handles”, and once the tag mechanism was exploited, the evolution towards complex life may have been much easier. [ABSTRACT FROM AUTHOR]

Background: Recent implementation of electronic health records (EHR) has dramatically changed medical ward organization. While residents in general internal medicine use EHR systems half of their working time, whether computer usage impacts residents’ workflow remains uncertain. We aimed to observe the frequency of task-switches occurring during resident’s work and to assess whether computer usage was associated with task-switching. Methods: In a large Swiss academic university hospital, we conducted, between May 26 and July 24, 2015 a time-motion study to assess how residents in general internal medicine organize their working day. Results: We observed 49 day and 17 evening shifts of 36 residents, amounting to 697 working hours. During day shifts, residents spent 5.4 hours using a computer (mean total working time: 11.6 hours per day). On average, residents switched 15 times per hour from a task to another. Task-switching peaked between 8:00–9:00 and 16:00–17:00. Task-switching was not associated with resident’s characteristics and no association was found between task-switching and extra hours (Spearman r = 0.220, p = 0.137 for day and r = 0.483, p = 0.058 for evening shifts). Computer usage occurred more frequently at the beginning or ends of day shifts and was associated with decreased overall task-switching. Conclusion: Task-switching occurs very frequently during resident’s working day. Despite the fact that residents used a computer half of their working time, computer usage was associated with decreased task-switching. Whether frequent task-switches and computer usage impact the quality of patient care and resident’s work must be evaluated in further studies. [ABSTRACT FROM AUTHOR]