Continuum mechanics modelling of microfilament networks with different architectures based on molecular investigation of single F-actin

The actin microfilament plays a critical role in many cellular processes including embryonic development, wound healing, immune response, and tissue development. It is commonly organized in the form of networks whose mechanical properties change with changes in their architecture due to cell evolution processes. This paper presents a new nonlinear continuum mechanics model of single filamentous actin (F-actin) that is based on nanoscale molecular simulations. Following this continuum model of the single F-actin, mechanical properties of differently architected lamellipodia are studied. The results provide insight that can contribute to the understanding of the cell edge motions of living cells.

Ion transport in small-molecule electrolytes based on LiI/3-hydroxypropionitrile with high salt contents

Abnormal “polymer-in-salt” conduction behavior is observed in a solid electrolyte composed of lithium iodide (LiI) and 3-hydroxypropionitrile (HPN). Based on comprehensive investigations by X-ray diffraction (XRD) and Raman and infrared spectroscopy, this abnormal conduction behavior is attributed to the formation of new ionic associates [Lim +In−]· · ·N C (m> n) and the reinforced hydrogen bonding of I· · ·HO in the electrolyte at high LiI concentrations.

Continuous and non-intrusive identity verification in real-time environments based on free-text keystroke dynamics

Internet services are important part of daily activities for most of us. These services come with sophisticated authentication requirements which may not be handled by average Internet users. The management of secure passwords for example creates an extra overhead which is often neglected due to usability reasons. Furthermore, password-based approaches are applicable only for initial logins and do not protect against unlocked workstation attacks. In this paper, we provide a non-intrusive identity verification scheme based on behavior biometrics where keystroke dynamics based-on free-text is used continuously for verifying the identity of a user in real-time. We improved existing keystroke dynamics based verification schemes in four aspects. First, we improve the scalability where we use a constant number of users instead of whole user space to verify the identity of target user. Second, we provide an adaptive user model which enables our solution to take the change of user behavior into consideration in verification decision. Next, we identify a new distance measure which enables us to verify identity of a user with shorter text. Fourth, we decrease the number of false results. Our solution is evaluated on a data set which we have collected from users while they were interacting with their mail-boxes during their daily activities.

A trusted ecosystem for Android applications based on context-aware access control

Private data stored on smartphones is a precious target for malware attacks. A constantly changing environment, e.g. switching network connections, can cause unpredictable threats, and require an adaptive approach to access control. Context-based access control is using dynamic environmental information, including it into access decisions. We propose an "ecosystem-in-an-ecosystem" which acts as a secure container for trusted software aiming at enterprise scenarios where users are allowed to use private devices. We have implemented a proof-of-concept prototype for an access control framework that processes changes to low-level sensors and semantically enriches them, adapting access control policies to the current context. This allows the user or the administrator to maintain fine-grained control over resource usage by compliant applications. Hence, resources local to the trusted container remain under control of the enterprise policy. Our results show that context-based access control can be done on smartphones without major performance impact.

Prediction of IBD based on population history for fine gene mapping

A novel multiple regression method (RM) is developed to predict identity-by-descent probabilities at a locus L (IBDL), among individuals without pedigree, given information on surrounding markers and population history. These IBDL probabilities are a function of the increase in linkage disequilibrium (LD) generated by drift in a homogeneous population over generations. Three parameters are sufficient to describe population history: effective population size (Ne), number of generations since foundation (T), and marker allele frequencies among founders (p). IBD L are used in a simulation study to map a quantitative trait locus (QTL) via variance component estimation. RM is compared to a coalescent method (CM) in terms of power and robustness of QTL detection. Differences between RM and CM are small but significant. For example, RM is more powerful than CM in dioecious populations, but not in monoecious populations. Moreover, RM is more robust than CM when marker phases are unknown or when there is complete LD among founders or Ne is wrong, and less robust when p is wrong. CM utilises all marker haplotype information, whereas RM utilises information contained in each individual marker and all possible marker pairs but not in higher order interactions. RM consists of a family of models encompassing four different population structures, and two ways of using marker information, which contrasts with the single model that must cater for all possible evolutionary scenarios in CM.

Investigation into the noise map based on traffic flow prediction in the citywide road network

As one of the measures for decreasing road traffic noise in a city, the control of the traffic flow and the physical distribution is considered. To conduct the measure effectively, the model for predicting the traffic flow in the citywide road network is necessary. In this study, the existing model named AVENUE was used as a traffic flow prediction model. The traffic flow model was integrated with the road vehicles' sound power model and the sound propagation model, and the new road traffic noise prediction model was established. As a case study, the prediction model was applied to the road network of Tsukuba city in Japan and the noise map of the city was made. To examine the calculation accuracy of the noise map, the calculated values of the noise at the main roads were compared with the measured values. As a result, it was found that there was a possibility that the high accuracy noise map of the city could be made by using the noise prediction model developed in this study.

Magnetic zeolite NaA : Synthesis, characterization based on metakaolin and its application for the removal of Cu2+, Pb2+

The optimum parameters for synthesis of zeolite NaA based on metakaolin were investigated according to results of cation exchange capacity and static water adsorption of all synthesis products and selected X-ray diffraction (XRD). Magnetic zeolite NaA was synthesized by adding Fe3O4 in the precursor of zeolite. Zeolite NaA and magnetic zeolite NaA were characterized with scanning electron microscopy (SEM) and XRD. Magnetic zeolite NaA with different Fe3O4 loadings was prepared and used for removal of heavy metals (Cu2+, Pb2+). The results show the optimum parameters for synthesis zeolite NaA are SiO2/Al2O3 = 2.3, Na2O/SiO2 = 1.4, H2O/Na2O = 50, crystallization time 8 h, crystallization temperature 95 �C. The addition of Fe3O4 makes the NaA zeolite with good magnetic susceptibility and good magnetic stability regardless of the Fe3O4 loading, confirming the considerable separation efficiency. Additionally, Fe3O4 loading had a little effect on removal of heavy metal by magnetic zeolite, however, the adsorption capacity still reaches 2.3 mmol g�1 for Cu2+, Pb2+ with a removal efficiency of over 95% in spite of 4.7% Fe3O4 loading. This indicates magnetic zeolite can be used to remove metal heavy at least Cu2+, Pb2+ from water with metallic contaminants and can be separated easily after a magnetic process.

Classification of railway bridges based on criticality and vulnerability factors

Bridges are currently rated individually for maintenance and repair action according to the structural conditions of their elements. Dealing with thousands of bridges and the many factors that cause deterioration, makes this rating process extremely complicated. The current simplified but practical methods are not accurate enough. On the other hand, the sophisticated, more accurate methods are only used for a single or particular bridge type. It is therefore necessary to develop a practical and accurate rating system for a network of bridges. The first most important step in achieving this aim is to classify bridges based on the differences in nature and the unique characteristics of the critical factors and the relationship between them, for a network of bridges. Critical factors and vulnerable elements will be identified and placed in different categories. This classification method will be used to develop a new practical rating method for a network of railway bridges based on criticality and vulnerability analysis. This rating system will be more accurate and economical as well as improve the safety and serviceability of railway bridges.

Extracting news blog hot topics based on the W2T methodology

Although topic detection and tracking techniques have made great progress, most of the researchers seldom pay more attention to the following two aspects. First, the construction of a topic model does not take the characteristics of different topics into consideration. Second, the factors that determine the formation and development of hot topics are not further analyzed. In order to correctly extract news blog hot topics, the paper views the above problems in a new perspective based on the W2T (Wisdom Web of Things) methodology, in which the characteristics of blog users, context of topic propagation and information granularity are investigated in a unified way. The motivations and features of blog users are first analyzed to understand the characteristics of news blog topics. Then the context of topic propagation is decomposed into the blog community, topic network and opinion network, respectively. Some important factors such as the user behavior pattern, opinion leader and network opinion are identified to track the development trends of news blog topics. Moreover, a blog hot topic detection algorithm is proposed, in which news blog hot topics are identified by measuring the duration, topic novelty, attention degree of users and topic growth. Experimental results show that the proposed method is feasible and effective. These results are also useful for further studying the formation mechanism of opinion leaders in blogspace.

A variable step-size FxLMS algorithm for feedforward active noise control systems based on a new online secondary path modelling technique

Several approaches have been introduced in literature for active noise control (ANC) systems. Since FxLMS algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of FxLMS algorithm. In many ANC applications an online secondary path modelling method using a white noise as a training signal is required to ensure convergence of the system. This paper also proposes a new approach for online secondary path modelling in feedfoward ANC systems. The proposed algorithm stops injection of the white noise at the optimum point and reactivate the injection during the operation, if needed, to maintain performance of the system. Benefiting new version of FxLMS algorithm and not continually injection of white noise makes the system more desirable and improves the noise attenuation performance. Comparative simulation results indicate effectiveness of the proposed approach.

A hydrogen/methane sensor based on niobium tungsten oxide nanorods synthesised by hydrothermal method

An investigation on hydrogen and methane sensing performance of hydrothermally formed niobium tungsten oxide nanorods employed in a Schottky diode structure is presented herein. By implementing tungsten into the surface of the niobium lattice, we create Nb5+ and W5+ oxide states and an abundant number of surface traps, which can collect and hold the adsorbate charge to reinforce a greater bending of the energy bands at the metal/oxide interface. We show experimentally, that extremely large voltage shifts can be achieved by these nanorods under exposure to gas at both room and high temperatures and attribute this to the strong accumulation of the dipolar charges at the interface via the surface traps. Thus, our results demonstrate that niobium tungsten oxide nanorods can be implemented for gas sensing applications, showing ultra-high sensitivities.

Hydrogen Gas Sensor Based on Highly Ordered Polyaniline/Multiwall Carbon Nanotubes Composite

In this work, the structural and gas sensing properties of an electropolymerized, polyaniline (PANI)/multiwall carbon nanotube (MWNT) composite based surface acoustic wave (SAW) sensor are reported. Thin films made of PANI nanofibers were deposited onto 36 lithium tantalate (LiTaO3) SAW transducers using electropolymerization and were subsequently dedoped. Scanning electron microscopy (SEM) revealed the compact growth of the composites which is much denser than that of PANI nanofibers. The PANI/MWNT composite based SAW sensor was then exposed to different concentrations of hydrogen (H2) gas at room temperature with a demonstrated electrical response.

Shahejie−Shahejie/Guantao/Wumishan and Carboniferous/Permian Coal−Paleozoic Total Petroleum Systems in the Bohaiwan Basin, China (based on geologic studies for the 2000 World Energy Assessment Project of the U.S. Geological Survey)

This report discusses the geologic framework and petroleum geology used to assess undiscovered petroleum resources in the Bohaiwan basin province for the 2000 World Energy Assessment Project of the U.S. Geological Survey. The Bohaiwan basin in northeastern China is the largest petroleum-producing region in China. Two total petroleum systems have been identified in the basin. The first, the Shahejie–Shahejie/Guantao/Wumishan Total Petroleum System, involves oil and gas generated from mature pods of lacustrine source rock that are associated with six major rift-controlled subbasins. Two assessment units are defined in this total petroleum system: (1) a Tertiary lacustrine assessment unit consisting of sandstone reservoirs interbedded with lacustrine shale source rocks, and (2) a pre-Tertiary buried hills assessment unit consisting of carbonate reservoirs that are overlain unconformably by Tertiary lacustrine shale source rocks. The second total petroleum system identified in the Bohaiwan basin is the Carboniferous/Permian Coal–Paleozoic Total Petroleum System, a hypothetical total petroleum system involving natural gas generated from multiple pods of thermally mature coal beds. Low-permeability Permian sandstones and possibly Carboniferous coal beds are the reservoir rocks. Most of the natural gas is inferred to be trapped in continuous accumulations near the center of the subbasins. This total petroleum system is largely unexplored and has good potential for undiscovered gas accumulations. One assessment unit, coal-sourced gas, is defined in this total petroleum system.

Hydrogen gas sensors based on thermally evaporated nanostructured MoO3 Schottky diode : a comparative study

In this paper, a comparative study of Pt/nanostructured MoO3/SiC Schottky diode based hydrogen gas sensors is presented. MoO3 nanostructured films with three different morphologies (nanoplatelets, nanoplateletsnanowires and nano-flowers) were deposited on SiC by thermal evaporation. We compare the current-voltage characteristics and the dynamic response of these sensors as they are exposed to hydrogen gas at temperatures up to 250°C. Results indicate that the sensor based on MoO3 nanoflowers exhibited the highest sensitivity (in terms of a 5.79V voltage shift) towards 1% hydrogen; while the sensor based on MoO3 nanoplatelets showed the quickest response (t90%- 40s).