Petascale molecular dynamics simulation using the fast multipole method on K computer

In this paper, we report all-atom simulations of molecular crowding — a result from the full node simulation on the “K computer”, which is a 10-PFLOPS supercomputer in Japan. The capability of this machine enables us to perform simulation of crowded cellular environments, which are more realistic compared to conventional MD simulations where proteins are simulated in isolation. Living cells are “crowded” because macromolecules comprise ∼30% of their molecular weight. Recently, the effects of crowded cellular environments on protein stability have been revealed through in-cell NMR spectroscopy. To measure the performance of the “K computer”, we performed all-atom classical molecular dynamics simulations of two systems: target proteins in a solvent, and target proteins in an environment of molecular crowders that mimic the conditions of a living cell. Using the full system, we achieved 4.4 PFLOPS during a 520 million-atom simulation with cutoff of 28 Å. Furthermore, we discuss the performance and scaling of fast multipole methods for molecular dynamics simulations on the “K computer”, as well as comparisons with Ewald summation methods.     

An efficient interface between the solvers of Maxwell’s equations and of the quasilinear kinetic equation for simulations of ion cyclotron heating in tokamak plasmas

Selfconsistent simulations of ion–cyclotron heating of tokamak plasmas require iterating between a solver of the wave equations in toroidal geometry and a solver of the Fokker–Planck equation describing the evolution of the ion distribution functions. A huge amount of information must be exchanged between the two codes at each iteration. For the package TORIC–SSFPQL, we have developed an interface which substantially reduces the CPU and memory requirements for the storage and transmission of these data. We present this interface here, and we take advantage of its efficiency to compare simulations in which the quasilinear diffusion operator in SSFPQL is evaluated superposing the TORIC results for all relevant toroidal modes excited by a given antenna with simulations using the fields of a single “representative” toroidal mode.     

Landslide identification and classification by object-based image analysis and fuzzy logic: An example from the Azdavay region (Kastamonu, Turkey)

This study presents a data-driven and semiautomatic classification system carried out by object-based image analysis and fuzzy logic in a selected landslide-prone area in the Western Black Sea region of Turkey. In the first stage, a multiresolution segmentation process was performed using Landsat ETM+ satellite images of the study area. The model was established on 5235 image objects obtained by the segmentation process. A total of 70 landslide locations and 10 input parameters including normalized difference vegetation index, slope angle, curvature, brightness, mean band blue, asymmetry, shape index, length/width ratio, gray level co-occurrence matrix, and mean difference to infrared band were considered in the analyses. Membership functions were used to classify the study area by five fuzzy operators such as “and”, “or”, “mean arithmetic”, “mean geometric”, and “algebraic product”. In order to assess the performances of the so-produced maps, 700 image objects, which were not used in the model, were taken into consideration. Based on the results, the map produced by “fuzzy and” operator performed better than those classified by the other fuzzy operators. The proposed methodology applied in this study may be useful for decision makers, local administrations, and scientists interested in landslides. It may also be useful in landslide-prone areas for planning, management, and regional development purposes.     

The effect of an information ethics course on the information ethics values of students - A Chinese guanxi culture perspective

The development of information technology has a significant influence on social structure and norms, and also impacts upon human behavior. In order to achieve stability and social harmony, people need to respect various norms, and have their rights protected. Students’ information ethics values are of critical and radical importance in achieving this goal. Using qualitative approach, the present study utilizes Kohlberg’s CMD model to measure improvement in students’ “information ethics values” through “technology mediated learning (TML)” models, and to assess the extent to which it is influenced by gender and Chinese guanxi culture. We find that while e-learning improves female students’ “respect rules,” “privacy,” “accessibility” and “intellectual property” values more than male students, the percentages relating to “intellectual property” for females in the higher stages remain lower than for males. Moreover, these results are interpreted from a Chinese guanxi culture perspective. In light of these results, educators should take account of such improvements when designing effective teaching methods and incentives.     

A novel ocean color index to detect floating algae in the global oceans

Various types of floating algae have been reported in open oceans and coastal waters, yet accurate and timely detection of these relatively small surface features using traditional satellite data and algorithms has been difficult or even impossible due to lack of spatial resolution, coverage, revisit frequency, or due to inherent algorithm limitations. Here, a simple ocean color index, namely the Floating Algae Index (FAI), is developed and used to detect floating algae in open ocean environments using the medium-resolution (250- and 500-m) data from operational MODIS (Moderate Resolution Imaging Spectroradiometer) instruments. FAI is defined as the difference between reflectance at 859 nm (vegetation “red edge”) and a linear baseline between the red band (645 nm) and short-wave infrared band (1240 or 1640 nm). Through data comparison and model simulations, FAI has shown advantages over the traditional NDVI (Normalized Difference Vegetation Index) or EVI (Enhanced Vegetation Index) because FAI is less sensitive to changes in environmental and observing conditions (aerosol type and thickness, solar/viewing geometry, and sun glint) and can “see” through thin clouds. The baseline subtraction method provides a simple yet effective means for atmospheric correction, through which floating algae can be easily recognized and delineated in various ocean waters, including the North Atlantic Ocean, Gulf of Mexico, Yellow Sea, and East China Sea. Because similar spectral bands are available on many existing and planned satellite sensors such as Landsat TM/ETM+ and VIIRS (Visible Infrared Imager/Radiometer Suite), the FAI concept is extendable to establish a long-term record of these ecologically important ocean plants.     

Output-feedback stabilization of an unstable wave equation

We consider the problem of stabilization of a one-dimensional wave equation that contains instability at its free end and control on the opposite end. In contrast to classical collocated “boundary damper” feedbacks for the neutrally stable wave equations with one end satisfying a homogeneous boundary condition, the controllers and the associated observers designed in the paper are more complex due to the open-loop instability of the plant. The controller and observer gains are designed using the method of “backstepping,” which results in explicit formulae for the gain functions. We prove exponential stability and the existence and uniqueness of classical solutions for the closed-loop system. We also derive the explicit compensators in frequency domain. The results are illustrated with simulations.     

Global sensitivity analysis of large-scale numerical landslide models based on Gaussian-Process meta-modeling

Large-scale landslide prediction is typically based on numerical modeling, with computer codes generally involving a large number of input parameters. Addressing the influence of each of them on the final result and providing a ranking procedure may be useful for risk management purposes. This can be performed by a variance-based global sensitivity analysis. Nevertheless, such an analysis requires a large number of computer code simulations, which appears impracticable for computationally demanding simulations, with computation times ranging from several hours to several days. To overcome this difficulty, we propose a “meta-model”-based strategy consisting in replacing the complex simulator by a “statistical approximation” provided by a Gaussian-process (GP) model. This allows computation of sensitivity measures from a limited number of simulations. For illustrative purposes, the proposed methodology is used to rank in terms of importance the properties of the elastoplastic model describing the complex behavior of the slip surface in the La Frasse landslide (Switzerland). One limitation of the GP-based methodology is that the computation of sensitivity measures is associated with uncertainty as the simulator is approximated using a training sample of small size, i.e., a limited knowledge on the “true” simulator. This source of uncertainty can be taken into account by treating the GP model from a Bayesian perspective. This provides the full posterior probability distribution associated with the sensitivity measures, which can be summarized by a confidence interval to outline the regions where the GP model is “unsure.” We show that this methodology is able to provide useful guidelines for the practical decision-making process and suggest further site investigations.     

VRML animated model watermarking scheme using geometry and interpolator nodes

Distinct from image and video watermarking, a watermarking scheme for 3D animation content is required in the 3D industry market for various applications. This paper develops a watermarking scheme for copyright protection and authentication of 3D animation content. A 3D animated model generally has a hierarchical structure with a number of transform nodes of a geometry node and an interpolator node for the timeline in contrast to a 3D polygon mesh model. The proposed scheme embeds not only a robust watermark into the geometry node for copyright protection but also a fragile watermark into the position and orientation interpolators for content authentication. We named the former “robust geometry watermarking” and the latter “fragile interpolator watermarking”. The proposed scheme performs the two watermarking schemes independently to realize simultaneously robust and fragile watermarked 3D animated model. Experimental results confirm that a watermark embedded by geometry watermarking robust to many attacks from commercial 3D editing tools while a watermark embedded by interpolator watermarking fragile to the same attacks.     

Robotic vocabulary building using extension inference and implicit contrast

TWIG (“Transportable Word Intension Generator”) is a system that allows a robot to learn compositional meanings for new words that are grounded in its sensory capabilities. The system is novel in its use of logical semantics to infer which entities in the environment are the referents (extensions) of unfamiliar words; its ability to learn the meanings of deictic (“I,” “this”) pronouns in a real sensory environment; its use of decision trees to implicitly contrast new word definitions with existing ones, thereby creating more complex definitions than if each word were treated as a separate learning problem; and its ability to use words learned in an unsupervised manner in complete grammatical sentences for production, comprehension, or referent inference. In an experiment with a physically embodied robot, TWIG learns grounded meanings for the words “I” and “you,” learns that “this” and “that” refer to objects of varying proximity, that “he” is someone talked about in the third person, and that “above” and “below” refer to height differences between objects. Follow-up experiments demonstrate the system's ability to learn different conjugations of “to be”; show that removing either the extension inference or implicit contrast components of the system results in worse definitions; and demonstrate how decision trees can be used to model shifts in meaning based on context in the case of color words.     

Overlapping model of beads and curve fitting of bead section for rapid manufacturing by robotic MAG welding process

As a deposition technology, robotic metal active gas (MAG) welding has shown new promises for rapid prototyping (RP) of metallic parts. During the process of forming metal parts with the robotic MAG welding technology, the sectional geometry of single-pass bead and the overlap of the adjacent beads have critical effects on the dimensional accuracy and quality of metal parts. In this work, Canny edge detection of the robotic MAG beads was carried out and the data were smoothed with a Gaussian filter and fitted with Gaussian function, logistic function, parabola function and sine function, respectively. In addition, a mathematical model of bead section was developed to analyze the bead geometry. Based on “surfacing of equivalent area” method, the concept of overlapping coefficient and optimum-overlapping coefficient was put forward, and calculated model of overlapping was analyzed. Optimal overlapping coefficient was calculated to be 63.66% under experimental condition. The conclusion is that the edge detection of bead section with Canny operator is continuous and distinct, and as compared with Gaussian function, logistic function and parabola function, sine function has higher accuracy to fit the measured data, and “surfacing of equivalent area” method shows to be rational and feasible by the experiments.     

Critical thermodynamic evaluation and optimization of the MnO–“ TiO2 ”–“ Ti2O3 ” system

A complete review, critical evaluation, and thermodynamic optimization of the phase equilibrium and thermodynamic properties of the MnO–“ TiO₂”–“ Ti₂O₃” systems at 1 bar pressure are presented. The molten oxide phase was described by the Modified Quasichemical Model. The Gibbs energy of spinel, pyrophanite and pseudobrookite solid solutions were modeled using the Compound Energy Formalism, and rutile solid solution was treated as a simple Henrian solution. Manganosite solid solution was assumed to dissolve both Ti⁴⁺ and Ti³⁺. A set of optimized model parameters for all phases was obtained which reproduces all available reliable thermodynamic and phase equilibrium data within experimental error limits from 25 ^°C to above the liquidus temperatures over the entire composition ranges and in the range of pO₂ from 10⁻²⁰ to 10⁻⁷ bar. Complex phase relationships in these systems have been elucidated, and discrepancies among the data have been resolved. The database of model parameters can be used along with software for Gibbs energy minimization in order to calculate any phase diagram section or thermodynamic properties.     

Recognition of handwritten Chinese characters by critical region analysis

The problem of recognizing offline handwritten Chinese characters has been investigated extensively. One difficulty is due to the existence of characters with very similar shapes. In this paper, we propose a “critical region analysis” technique which highlights the critical regions that distinguish one character from another similar character. The critical regions are identified automatically based on the output of the Fisher's discriminant. Additional features are extracted from these regions and contribute to the recognition process. By incorporating this technique into the character recognition system, a record high recognition rate of 99.53% on the ETL-9B database is obtained.     

Mining sentiments in SMS texts for teaching evaluation

This paper explores the potential application of sentiment mining for analyzing short message service (SMS) texts in teaching evaluation. Data preparation involves the reading, parsing and categorization of the SMS texts. Three models were developed: the base model, the “corrected” model which adjusts for spelling errors and the “sentiment” model which extends the “corrected” model by performing sentiment mining. An “interestingness” criterion selects the “sentiment” model from which the sentiments of the students towards the lecture are discerned. Two types of incomplete SMS texts are also identified and the implications of their removal for the analysis ascertained.     

A uniform rationale for Whitney forms on various supporting shapes

A method for constructing Whitney forms is proposed, which applies to tetrahedra, hexahedra, triangular prisms, and pyramids in a similar way, and proceeds from a unique generating principle, thus unifying their presentation. The principle automatically enforces conformity (i.e., “tangential” or “normal continuity” of the elementary proxy fields) at element interfaces, and generates a complex of forms with the “exact sequence property” built in.     

Gas–liquid dynamics at low Reynolds numbers in pillared rectangular micro channels

Most heterogeneously catalyzed gas–liquid reactions in micro channels are chemically/kinetically limited because of the high gas–liquid and liquid–solid mass transfer rates that can be achieved. This motivates the design of systems with a larger surface area, which can be expected to offer higher reaction rates per unit volume of reactor. This increase in surface area can be realized by using structured micro channels. In this work, rectangular micro channels containing round pillars of 3 μm in diameter and 50 μm in height are studied. The flow regimes, gas hold-up, and pressure drop are determined for pillar pitches of 7, 12, 17, and 27 μm. Flow maps are presented and compared with flow maps of rectangular and round micro channels without pillars. The Armand correlation predicts the gas hold-up in the pillared micro channel within 3% error. Three models are derived which give the single-phase and the two-phase pressure drop as a function of the gas and liquid superficial velocities and the pillar pitches. For a pillar pitch of 27 μm, the Darcy-Brinkman equation predicts the single-phase pressure drop within 2% error. For pillar pitches of 7, 12, and 17 μm, the Blake-Kozeny equation predicts the single-phase pressure drop within 20%. The two-phase pressure drop model predicts the experimental data within 30% error for channels containing pillars with a pitch of 17 μm, whereas the Lockhart–Martinelli correlation is proven to be non-applicable for the system used in this work. The open structure and the higher production rate per unit of reactor volume make the pillared micro channel an efficient system for performing heterogeneously catalyzed gas–liquid reactions.     

Critical thermodynamic evaluation and optimization of the MnO–SiO2–“ TiO2 ”–“ Ti2O3 ” system

A complete review, critical evaluation, and thermodynamic optimization of phase equilibrium and thermodynamic properties of the MnO–SiO₂–“ TiO₂”–“ Ti₂O₃” systems at 1 bar pressure are presented. The molten oxide phase was described by the Modified Quasichemical Model. The Gibbs energies of the manganosite, spinel, pyrophanite and pseudobrookite and rutile solid solutions were taken from the previous study. A set of optimized model parameters for the molten oxide phase was obtained which reproduces all available reliable thermodynamic and phase equilibrium data within experimental error limits from 25 ^°C to above the liquidus temperatures over the entire range of compositions and oxygen partial pressure in the range of pO₂ from 10⁻²⁰ bar to 10⁻⁷ bar. Complex phase relationships in these systems have been elucidated, and discrepancies among the data have been resolved. The database of model parameters can be used along with software for Gibbs energy minimization in order to calculate any phase diagram section or thermodynamic properties.     

A mathematical model on EPQ for stochastic demand in an imperfect production system

In the paper, we develop an EPQ (economic production quantity) inventory model to determine the optimal buffer inventory for stochastic demand in the market during preventive maintenance or repair of a manufacturing facility with an EPQ (economic production quantity) model in an imperfect production system. Preventive maintenance, an essential element of the just-in-time structure, may cause shortage which is reduced by buffer inventory. The products are sold with the free minimal repair warranty (FRW) policy. The production system may undergo “out-of-control” state from “in-control” state, after a certain time that follows a probability density function. The defective (non-conforming) items in “in-control” or “out-of-control” state are reworked at a cost just after the regular production time. Finally, an expected cost function regarding the inventory cost, unit production cost, preventive maintenance cost and shortage cost is minimized analytically. We develop another case where the buffer inventory as well as the production rate are decision variables and the expected unit cost considering the above cost functions is optimized also. The numerical examples are provided to illustrate the behaviour and application of the model. Sensitivity analysis of the model with respect to key parameters of the system is carried out.     

Solving a non-linear model: The importance of model specification for deriving a suitable solution

In this paper, we consider a macroeconomic model with alternative linear and non-linear specifications. One version of the model, expressed in levels, is highly non-linear and has at least two steady-state equilibria. One of these equilibria has an economically meaningful interpretation, while the other does not have a sensible economic interpretation. A second version of the model, expressed in logarithms, is linear and has a unique steady-state equilibrium, which corresponds to the economically meaningful equilibrium of the non-linear version of the model. The dynamic solution of each model version has a combination of stable and unstable eigenvalues so that any dynamic solution requires the calculation of appropriate “jumps” in endogenous variables. Attempts to solve these models, using forward-shooting and reverse-shooting algorithms, show that the forward-shooting algorithm chooses the “wrong” solution for the non-linear model, but the “right” solution for the linear model. The reverse-shooting algorithm chooses the “right” solution in both cases. We demonstrate how this result is driven by particular properties of the two versions of the model.     

Critical conditions and breakup of non-squashed microconfined droplets: effects of fluid viscoelasticity

Droplet breakup in systems with either a viscoelastic matrix or a viscoelastic droplet is studied microscopically in bulk and confined shear flow, using a parallel plate counter rotating shear flow cell. The ratio of droplet diameter to gap spacing is systematically varied between 0.1 and 0.85. In bulk shear flow, the effects of matrix and droplet viscoelasticity on the critical capillary number for breakup are very moderate under the studied conditions. However, in confined conditions a profoundly different behaviour is observed: the critical capillary numbers of a viscoelastic droplet are similar to those of a Newtonian droplet, whereas matrix viscoelasticity causes breakup at a much lower capillary number. The critical capillary numbers are compared with the predictions of a phenomenological model by Minale et al. (Langmuir 26:126–132, 2010); the model results are in qualitative disagreement with the experimental data. It is also found that the critical dimensionless droplet length, the critical capillary number, and the dimensionless droplet length at breakup show a similar dependency on confinement ratio. As a result, confined droplets in a viscoelastic matrix have a smaller dimensionless length at breakup than droplets in a Newtonian matrix, which affects the breakup mode. Whereas confined droplets in a Newtonian matrix can break up into multiple parts, only two daughter droplets are obtained after breakup in a viscoelastic matrix, up to very large confinement ratios.     

Marginal analysis of multivariate failure time data with a surviving fraction based on semiparametric transformation cure models

In biomedical, genetic and social studies, there may exist a fraction of individuals not experiencing the event of interest such that the survival curves eventually level off to nonzero proportions. These people are referred to as “cured” or “nonsusceptible” individuals. Models that have been developed to address this issue are known as cured models. The mixture model, which consists of a model for the binary cure status and a survival model for the event times of the noncured individuals, is one of the widely used cure models. In this paper, we propose a class of semiparametric transformation cure models for multivariate survival data with a surviving fraction by fitting a logistic regression model to the cure status and a semiparametric transformation model to the event time of the noncured individual. Both models allow incorporating covariates and do not require any assumption of the association structure. The statistical inference is based on the marginal approach by constructing a system of estimating equations. The asymptotic properties of the proposed estimators are proved, and the performance of the estimation is demonstrated via simulations. In addition, the approach is illustrated by analyzing the smoking cessation data.