An ensemble method for predicting subnuclear localizations from primary protein structures

Background Predicting protein subnuclear localization is a challenging problem. Some previous works based on non-sequence information including Gene Ontology annotations and kernel fusion have respective limitations. The aim of this work is twofold: one is to propose a novel individual feature extraction method; another is to develop an ensemble method to improve prediction performance using comprehensive information represented in the form of high dimensional feature vector obtained by 11 feature extraction methods. Methodology/Principal Findings A novel two-stage multiclass support vector machine is proposed to predict protein subnuclear localizations. It only considers those feature extraction methods based on amino acid classifications and physicochemical properties. In order to speed up our system, an automatic search method for the kernel parameter is used. The prediction performance of our method is evaluated on four datasets: Lei dataset, multi-localization dataset, SNL9 dataset and a new independent dataset. The overall accuracy of prediction for 6 localizations on Lei dataset is 75.2% and that for 9 localizations on SNL9 dataset is 72.1% in the leave-one-out cross validation, 71.7% for the multi-localization dataset and 69.8% for the new independent dataset, respectively. Comparisons with those existing methods show that our method performs better for both single-localization and multi-localization proteins and achieves more balanced sensitivities and specificities on large-size and small-size subcellular localizations. The overall accuracy improvements are 4.0% and 4.7% for single-localization proteins and 6.5% for multi-localization proteins. The reliability and stability of our classification model are further confirmed by permutation analysis. Conclusions It can be concluded that our method is effective and valuable for predicting protein subnuclear localizations. A web server has been designed to implement the proposed method. It is freely available at http://bioinformatics.awowshop.com/snlpr​ed_page.php.

The development of a new method for the determination of concentrations of carbonaceous gases using a non-dispersive infrared sensor

An analytical method for the detection of carbonaceous gases by a non-dispersive infrared sensor (NDIR) has been developed. The calibration plots of six carbonaceous gases including CO2, CH4, CO, C2H2, C2H4 and C2H6 were obtained and the reproducibility determined to verify the feasibility of this gas monitoring method. The results prove that squared correlation coefficients for the six gas measurements are greater than 0.999. The reproducibility is excellent, thus indicating that this analytical method is useful to determinate the concentrations of carbonaceous gases.

Valid and reliable assessment of wellness among adolescents : do you know what you’re measuring?

Measuring wellness among adolescents is an emerging trend among professionals and researchers endeavouring to influence youth as they establish lifestyle patterns in this critical period of life. This discussion highlights instruments used to measure wellness among adolescents, and considers the empirical data supporting their validity and reliability amongst adolescents. In summary, Adolescent wellness is an important indicator of future health and lifestyle habits. There are a number of tools available to measure wellness, each with its own focus, depending on the definition or model from which it was developed. This may cause debate regarding the appropriateness of some instruments for evaluating wellness. The majority of wellness evaluation approaches reported among adolescents have less than ideal validation. A ‘gold standard’ definition could lead to the standardisation of a theoretical model against which wellness instruments could be validated. The absence of peer reviewed studies reporting psychometric testing for wellness evaluation instruments among adolescents is concerning given their growing popularity and highlights a priority area for future research in this field.

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.

Conceptualising, operationalising and measuring the player experience in videogames

The player experience is at the core of videogame play. Understanding the facets of player experience presents many research challenges, as the phenomenon sits at the intersection of psychology, design, human-computer interaction, sociology, and physiology. This workshop brings together an interdisciplinary group of researchers to systematically and rigorously analyse all aspects of the player experience. Methods and tools for conceptualising, operationalising and measuring the player experience form the core of this research. Our aim is to take a holistic approach to identifying, adapting and extending theories and models of the player experience, to understand how these theories and models interact, overlap and differ, and to construct a unified vision for future research.

A wide area monitoring system based load restoration method

Restoring a large-scale power system has always been a complicated and important issue. A lot of research work has been done on different aspects of the whole power system restoration procedure. However, more time will be required to complete the power system restoration process in an actual situation if accurate and real-time system data cannot be obtained. With the development of the wide area monitoring system (WAMS), power system operators are capable of accessing to more accurate data in the restoration stage after a major outage. The ultimate goal of the system restoration is to restore as much load as possible while in the shortest period of time after a blackout, and the restorable load can be estimated by employing WAMS. Moreover, discrete restorable loads are employed considering the limited number of circuit-breaker operations and the practical topology of distribution systems. In this work, a restorable load estimation method is proposed employing WAMS data after the network frame has been reenergized, and WAMS is also employed to monitor the system parameters in case the newly recovered system becomes unstable again. The proposed method has been validated with the New England 39-Bus system and an actual power system in Guangzhou, China.

Shear design of cold-formed steel beams using direct strength method

This paper presents the direct strength method (DSM) equations for cold-formed steel beams subject to shear. Light gauge cold-formed steel sections have been developed as more economical building solutions to the alternative heavier hot-rolled sections in the commercial and residential markets. Cold-formed lipped channel beams (LCB), LiteSteel beams (LSB) and hollow flange beams (HFB) are commonly used as flexural members such as floor joists and bearers. However, their shear capacities are determined based on conservative design rules. For the shear design of cold-formed web panels, their elastic shear buckling strength must be determined accurately including the potential post-buckling strength. Currently the elastic shear buckling coefficients of web panels are determined by assuming conservatively that the web panels are simply supported at the junction between the flange and web elements and ignore the post-buckling strength. Hence experimental and numerical studies were conducted to investigate the shear behaviour and strength of LSBs, LCBs and HFBs. New direct strength method (DSM) based design equations were proposed to determine the ultimate shear capacities of cold-formed steel beams. An improved equation for the higher elastic shear buckling coefficient of cold-formed steel beams was proposed based on finite element analysis results and included in the DSM design equations. A new post-buckling coefficient was also introduced in the DSM equation to include the available post-buckling strength of cold-formed steel beams.

A note on the ‘Linsanity’ of measuring the relative efficiency of National Basketball Association guards

This note examines the productive efficiency of 62 starting guards during the 2011/12 National Basketball Association (NBA) season. This period coincides with the phenomenal and largely unanticipated performance of New York Knicks’ starting point guard Jeremy Lin and the attendant public and media hype known as Linsanity. We employ a data envelopment analysis (DEA) approach that includes allowance for an undesirable output, here turnovers per game, with the desirable outputs of points, rebounds, assists, steals and blocks per game and an input of minutes per game. The results indicate that depending upon the specification, between 29% and 42% of NBA guards are fully efficient, including Jeremy Lin, with a mean inefficiency of 3.7% and 19.2%. However, while Jeremy Lin is technically efficient, he seldom serves as a benchmark for inefficient players, at least when compared with established players such as Chris Paul and Dwayne Wade. This suggests the uniqueness of Jeremy Lin's productive solution and may explain why his unique style of play, encompassing individual brilliance, unselfish play and team leadership, is of such broad public appeal.

A new online secondary path modelling method for feedforward active noise control systems

An online secondary path modelling method using a white noise as a training signal is required in many applications of active noise control (ANC) to ensure convergence of the system. Not continually injection of white noise during system operation makes the system more desirable. The purposes of the proposed method are two folds: controlling white noise by preventing continually injection, and benefiting white noise with a larger variance. The modelling accuracy and the convergence rate increase when a white noise with larger variance is used, however larger the variance increases the residual noise, which decreases performance of the system. This paper proposes a new approach for online secondary path modelling in feedfoward ANC systems. The proposed algorithm uses the advantages of the white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the system. Comparative simulation results shown in this paper indicate effectiveness of the proposed approach in controlling active noise.

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.

Pressure ulcers in the adult intensive care unit : a literature review of patient risk factors and risk assessment scales

Background: Critically ill patients are at high risk for pressure ulcer (PrU) development due to their high acuity and the invasive nature of the multiple interventions and therapies they receive. With reported incidence rates of PrU development in the adult critical care population as high as 56%, the identification of patients at high risk of PrU development is essential. This paper will explore the association between PrU development and risk factors. It will also explore PrU development and the use of risk assessment scales for critically ill patients in adult intensive care units. Method: A literature search from 2000 to 2012 using the CINHAL, Cochrane Library, EBSCOHost, Medline (via EBSCOHost), PubMed, ProQuest and Google Scholar databases was conducted. Key words used were: pressure ulcer/s; pressure sore/s; decubitus ulcer/s; bed sore/s; critical care; intensive care; critical illness; prevalence; incidence; prevention; management; risk factor; risk assessment scale. Results: Nineteen articles were included in this review; eight studies addressing PrU risk factors, eight studies addressing risk assessment scales and three studies overlapping both. Results from the studies reviewed identified 28 intrinsic and extrinsic risk factors which may lead to PrU development. Development of a risk factor prediction model in this patient population, although beneficial, appears problematic due to many issues such as diverse diagnoses and subsequent patient needs. Additionally, several risk assessment instruments have been developed for early screening of patients at higher risk of developing PrU in the ICU. No existing risk assessment scales are valid for identification high risk critically ill patient,with the majority of scales potentially over-predicting patients at risk for PrU development. Conclusion: Research studies to inform the risk factors for potential pressure ulcer development are inconsistent. Additionally, there is no consistent or clear evidence which demonstrates any scale to better or more effective than another when used to identify the patients at risk for PrU development. Furthermore robust research is needed to identify the risk factors and develop valid scales for measuring the risk of PrU development in ICU.

Destination brand equity for Australia : testing a model of CBBE in short haul and long haul markets

The study of destination brand performance measurement has only emerged in earnest as a field in the tourism literature since 2007. The concept of consumer-based brand equity (CBBE) is gaining favour from services marketing researchers as an alternative to the traditional ‘net-present-value of future earnings’ method of measuring brand equity. The perceptions-based CBBE model also appears suitable for examining destination brand performance, where a financial brand equity valuation on a destination marketing organisation’s (DMO) balance sheet is largely irrelevant. This is the first study to test and compare the model in both short and long haul markets. The paper reports the results of tests of a CBBE model for Australia in a traditional short haul market (New Zealand) and an emerging long haul market (Chile). The data from both samples indicated destination brand salience, brand image, and brand value are positively related to purchase intent for Australia in these two disparate markets.

Damage assessment in reinforced concrete flexural members using modal strain energy based method

Damage assessment (damage detection, localization and quantification) in structures and appropriate retrofitting will enable the safe and efficient function of the structures. In this context, many Vibration Based Damage Identification Techniques (VBDIT) have emerged with potential for accurate damage assessment. VBDITs have achieved significant research interest in recent years, mainly due to their non-destructive nature and ability to assess inaccessible and invisible damage locations. Damage Index (DI) methods are also vibration based, but they are not based on the structural model. DI methods are fast and inexpensive compared to the model-based methods and have the ability to automate the damage detection process. DI method analyses the change in vibration response of the structure between two states so that the damage can be identified. Extensive research has been carried out to apply the DI method to assess damage in steel structures. Comparatively, there has been very little research interest in the use of DI methods to assess damage in Reinforced Concrete (RC) structures due to the complexity of simulating the predominant damage type, the flexural crack. Flexural cracks in RC beams distribute non- linearly and propagate along all directions. Secondary cracks extend more rapidly along the longitudinal and transverse directions of a RC structure than propagation of existing cracks in the depth direction due to stress distribution caused by the tensile reinforcement. Simplified damage simulation techniques (such as reductions in the modulus or section depth or use of rotational spring elements) that have been extensively used with research on steel structures, cannot be applied to simulate flexural cracks in RC elements. This highlights a big gap in knowledge and as a consequence VBDITs have not been successfully applied to damage assessment in RC structures. This research will address the above gap in knowledge and will develop and apply a modal strain energy based DI method to assess damage in RC flexural members. Firstly, this research evaluated different damage simulation techniques and recommended an appropriate technique to simulate the post cracking behaviour of RC structures. The ABAQUS finite element package was used throughout the study with properly validated material models. The damaged plasticity model was recommended as the method which can correctly simulate the post cracking behaviour of RC structures and was used in the rest of this study. Four different forms of Modal Strain Energy based Damage Indices (MSEDIs) were proposed to improve the damage assessment capability by minimising the numbers and intensities of false alarms. The developed MSEDIs were then used to automate the damage detection process by incorporating programmable algorithms. The developed algorithms have the ability to identify common issues associated with the vibration properties such as mode shifting and phase change. To minimise the effect of noise on the DI calculation process, this research proposed a sequential order of curve fitting technique. Finally, a statistical based damage assessment scheme was proposed to enhance the reliability of the damage assessment results. The proposed techniques were applied to locate damage in RC beams and slabs on girder bridge model to demonstrate their accuracy and efficiency. The outcomes of this research will make a significant contribution to the technical knowledge of VBDIT and will enhance the accuracy of damage assessment in RC structures. The application of the research findings to RC flexural members will enable their safe and efficient performance.

An optimized online secondary path modeling method for single-channel feedback ANC systems

This paper proposes a new method for online secondary path modeling in feedback active noise control (ANC) systems. In practical cases, the secondary path is usually time varying. For these cases, online modeling of secondary path is required to ensure convergence of the system. In literature the secondary path estimation is usually performed offline, prior to online modeling, where in the proposed system there is no need for using offline estimation. The proposed method consists of two steps: a noise controller which is based on an FxLMS algorithm, and a variable step size (VSS) LMS algorithm which is used to adapt the modeling filter with the secondary path. In order to increase performance of the algorithm in a faster convergence and accurate performance, we stop the VSS-LMS algorithm at the optimum point. The results of computer simulation shown in this paper indicate effectiveness of the proposed method.