Identifying influential users of micro-blogging services : a dynamic action-based network approach

In this paper, we present a dynamic model to identify influential users of micro-blogging services. Micro-blogging services, such as Twitter, allow their users (twitterers) to publish tweets and choose to follow other users to receive tweets. Previous work on user influence on Twitter, concerns more on following link structure and the contents user published, seldom emphasizes the importance of interactions among users. We argue that, by emphasizing on user actions in micro-blogging platform, user influence could be measured more accurately. Since micro-blogging is a powerful social media and communication platform, identifying influential users according to user interactions has more practical meanings, e.g., advertisers may concern how many actions – buying, in this scenario – the influential users could initiate rather than how many advertisements they spread. By introducing the idea of PageRank algorithm, innovatively, we propose our model using action-based network which could capture the ability of influential users when they interacting with micro-blogging platform. Taking the evolving prosperity of micro-blogging into consideration, we extend our actionbaseduser influence model into a dynamic one, which could distinguish influential users in different time periods. Simulation results demonstrate that our models could support and give reasonable explanations for the scenarios that we considered.

A new look at the restrictions on the speed and magnitude of train loads for bridge management

In current bridge management systems (BMSs), load and speed restrictions are applied on unhealthy bridges to keep the structure safe and serviceable for as long as possible. But the question is, whether applying these restrictions will always decrease the internal forces in critical components of the bridge and enhance the safety of the unhealthy bridges. To find the answer, this paper for the first time in literature, looks into the design aspects through studying the changes in demand by capacity ratios of the critical components of a bridge under the train loads. For this purpose, a structural model of a simply supported bridge, whose dynamic behaviour is similar to a group of real railway bridges, is developed. Demand by capacity ratios of the critical components of the bridge are calculated, to identify their sensitivity to increase of speed and magnitude of live load. The outcomes of this study are very significant as they show that, on the contrary to what is expected, by applying restriction on speed, the demand by capacity ratio of components may increase and make the bridge unsafe for carrying live load. Suggestions are made to solve the problem.

Injection velocity control of thermoplastic injection molding via a double controller scheme

Injection velocity has been recognized as a key variable in thermoplastic injection molding. Its closed-loop control is, however, difficult due to the complexity of the process dynamic characteristics. The basic requirements of the control system include tracking of a pre-determined injection velocity curve defined in a profile, load rejection and robustness. It is difficult for a conventional control scheme to meet all these requirements. Injection velocity dynamics are first analyzed in this paper. Then a novel double-controller scheme is adopted for the injection velocity control. This scheme allows an independent design of set-point tracking and load rejection and has good system robustness. The implementation of the double-controller scheme for injection velocity control is discussed. Special techniques such as profile transformation and shifting are also introduced to improve the velocity responses. The proposed velocity control has been experimentally demonstrated to be effective for a wide range of processing conditions.

The effectiveness of information-sharing interventions to reduce anxiety in families waiting for surgical patients undergoing an elective surgical procedure: A systematic review

Background Whilst waiting for patients undergoing surgery, a lack of information regarding the patient’s status and the outcome of surgery, can contribute to the anxiety experienced by family members. Effective strategies for providing information to families are therefore required. Objectives To synthesize the best available evidence in relation to the most effective information-sharing interventions to reduce anxiety for families waiting for patients undergoing an elective surgical procedure. Inclusion criteria Types of participants All studies of family members over 18 years of age waiting for patients undergoing an elective surgical procedure were included, including those waiting for both adult and pediatric patients.   Types of intervention All information-sharing interventions for families of patients undergoing an elective surgical procedure were eligible for inclusion in the review. Types of studies All randomized controlled trials (RCTs) quasi-experimental studies, case-controlled and descriptive studies, comparing one information-sharing intervention to another or to usual care were eligible for inclusion in the review. Types of outcomes Primary outcome: The level of anxiety amongst family members or close relatives whilst waiting for patients undergoing surgery, as measured by a validated instrument such as the S-Anxiety portion of the State-Trait Anxiety Inventory (STAI). Secondary outcomes: Family satisfaction and other measurements that may be considered indicators of stress and anxiety, such as mean arterial pressure (MAP) and heart rate. Search strategy A comprehensive search, restricted to English language only, was undertaken of the following databases from 1990 to May 2013: Medline, CINAHL, EMBASE, ProQuest, Web of Science, PsycINFO, Scopus, Dissertation and Theses PQDT (via ProQuest), Current Contents, CENTRAL, Google Scholar, OpenGrey, Clinical Trials, Science.gov, Current Controlled Trials and National Institute for Clinical Studies (NHMRC). Methodological quality Two independent reviewers critically appraised retrieved papers for methodological quality using the standardized critical appraisal instruments for randomized controlled trials and descriptive studies from the Joanna Briggs Institute Meta Analysis of Statistics Assessment and Review Instruments (JBI-MAStARI). Data extraction Two independent reviewers extracted data from included papers using a customized data extraction form. Data synthesis Statistical pooling was not possible, mainly due to issues with data reporting in two of the studies, therefore the results are presented in narrative form. Results Three studies with a total of 357 participants were included in the review. In-person reporting to family members was found to be effective in comparison with usual care in which no reports were provided. Telephone reporting was also found to be effective at reducing anxiety, in comparison with usual care, although not as effective as in-person reporting. The use of paging devices to keep family members informed were found to increase, rather than decrease anxiety. Conclusions Due to the lack of high quality research in this area, the strength of the conclusions are limited. It appears that in-person and telephone reporting to family members decreases anxiety, however the use of paging devices increases anxiety.

Dynamic capabilities and performance : an empirical study of audiovisual producers in Europe

This study tests Teece’s conceptualization of dynamic capabilities in the context of small and medium sized firms competing in creative industries, i.e. the European audio-visual production industry. This industry is characterized by immature and evolving markets where firms’ dynamic capabilities are expected to lead to superior innovative performance. Using survey data from audio-visual producers in ten European countries we find that both sensing and seizing capabilities have a positive effect on firms' innovative performance. The effect however, is curvilinear and positive effects appear only when capabilities overcome a threshold level.

Dynamic simulation of CFRP strengthened steel column under impact loading

Carbon fibre reinforced polymer (CFRP) strengthening of metallic structures under static loading has shown great potential in the recent years. However, steel structures are often experienced natural (e.g. earthquake, wind) as well as man-made (e.g. vehicular impact, blast) dynamic loading. Therefore, there is a growing interest among the researchers to investigate the capability of CFRP strengthened members under such dynamic conditions. This study focuses on the finite element (FE) numerical modelling and simulation of CFRP strengthened steel column under transverse impact loading to predict the behaviour and failure modes. Impact simulation process and the CFRP strengthened steel column are validated with the existing experimental results in literature. The validated FE model of CFRP strengthened steel column is then further used to investigate the effects of transverse impact loading on its structural performance. The results are presented in terms of transvers e impact force, lateral and axial displacement, and deformed shape to evaluate the effectiveness of CFRP strengthening technique. Comparisons between the bare steel and CFRP strengthened steel columns clearly indicate the performance enhancement of strengthened column under transverse impact loading.

Transit route occupancy load factor and passenger average travel time for quality of service assessment

This paper investigates quality of service (QoS) and resource productivity implications of transit route passenger loading and travel time. It highlights the value of occupancy load factor as a direct passenger comfort QoS measure. Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia, is used to investigate time series correlation between occupancy load factor and passenger average travel time. Correlation is strong across the entire span of service in both directions. Passengers tend to be making longer, peak direction commuter trips under significantly less comfortable conditions than off-peak. The Transit Capacity and Quality of Service Manual uses segment based load factor as a measure of onboard loading comfort QoS. This paper provides additional insight into QoS by relating the two route based dimensions of occupancy load factor and passenger average travel time together in a two dimensional format, both from the passenger’s and operator’s perspectives. Future research will apply Value of Time to QoS measurement, reflecting perceived passenger comfort through crowding and average time spent onboard. This would also assist in transit service quality econometric modeling. The methodology can be readily applied in a practical setting where AFC data for fixed scheduled routes is available. The study outcomes also provide valuable research and development directions.

Transit route occupancy load factor and passenger average travel time for quality of service assessment

This presentation investigates quality of service (QoS) and resource productivity implications of transit route passenger loading and travel time. It highlights the value of occupancy load factor as a direct passenger comfort QoS measure. Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia, is used to investigate time series correlation between occupancy load factor and passenger average travel time. Correlation is strong across the entire span of service in both directions. Passengers tend to be making longer, peak direction commuter trips under significantly less comfortable conditions than off-peak. The Transit Capacity and Quality of Service Manual uses segment based load factor as a measure of onboard loading comfort QoS. This paper provides additional insight into QoS by relating the two route based dimensions of occupancy load factor and passenger average travel time together in a two dimensional format, both from the passenger’s and operator’s perspectives. Future research will apply Value of Time to QoS measurement, reflecting perceived passenger comfort through crowding and average time spent onboard. This would also assist in transit service quality econometric modeling. The methodology can be readily applied in a practical setting where AFC data for fixed scheduled routes is available. The study outcomes also provide valuable research and development directions.

Stochastic analysis of transit route segments' passenger load variation for capacity and quality of service assessment

This paper investigates stochastic analysis of transit segment hourly passenger load factor variation for transit capacity and quality of service (QoS) analysis using Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia. It compares stochastic analysis to traditional peak hour factor (PHF) analysis to gain further insight into variability of transit route segments’ passenger loading during a study hour. It demonstrates that hourly design load factor is a useful method of modeling a route segment’s capacity and QoS time history across the study weekday. This analysis method is readily adaptable to different passenger load standards by adjusting design percentile, reflecting either a more relaxed or more stringent condition. This paper also considers hourly coefficient of variation of load factor as a capacity and QoS assessment measure, in particular through its relationships with hourly average and design load factors. Smaller value reflects uniform passenger loading, which is generally indicative of well dispersed passenger boarding demands and good schedule maintenance. Conversely, higher value may be indicative of pulsed or uneven passenger boarding demands, poor schedule maintenance, and/or bus bunching. An assessment table based on hourly coefficient of variation of load factor is developed and applied to this case study. Inferences are drawn for a selection of study hours across the weekday studied.

Stochastic analysis of transit route segments' passenger load variation for capacity & quality of service assessment

This study uses weekday Automatic Fare Collection (AFC) data on a premium bus line in Brisbane, Australia •Stochastic analysis is compared to peak hour factor (PHF) analysis for insight into passenger loading variability •Hourly design load factor (e.g. 88th percentile) is found to be a useful method of modeling a segment’s passenger demand time-history across a study weekday, for capacity and QoS assessment •Hourly coefficient of variation of load factor is found to be a useful QoS and operational assessment measure, particularly through its relationship with hourly average load factor, and with design load factor •An assessment table based on hourly coefficient of variation of load factor is developed from the case study

Models of protein linear molecular motors for dynamic nanodevices

Protein molecular motors are natural nano-machines that convert the chemical energy from the hydrolysis of adenosine triphosphate into mechanical work. These efficient machines are central to many biological processes, including cellular motion, muscle contraction and cell division. The remarkable energetic efficiency of the protein molecular motors coupled with their nano-scale has prompted an increasing number of studies focusing on their integration in hybrid micro- and nanodevices, in particular using linear molecular motors. The translation of these tentative devices into technologically and economically feasible ones requires an engineering, design-orientated approach based on a structured formalism, preferably mathematical. This contribution reviews the present state of the art in the modelling of protein linear molecular motors, as relevant to the future design-orientated development of hybrid dynamic nanodevices. © 2009 The Royal Society of Chemistry.

Decision making in social neurobiological systems modeled as transitions in dynamic pattern formation

Extant models of decision making in social neurobiological systems have typically explained task dynamics as characterized by transitions between two attractors. In this paper, we model a three-attractor task exemplified in a team sport context. The model showed that an attacker–defender dyadic system can be described by the angle x between a vector connecting the participants and the try line. This variable was proposed as an order parameter of the system and could be dynamically expressed by integrating a potential function. Empirical evidence has revealed that this kind of system has three stable attractors, with a potential function of the form V(x)=−k1x+k2ax2/2−bx4/4+x6/6, where k1 and k2 are two control parameters. Random fluctuations were also observed in system behavior, modeled as white noise εt, leading to the motion equation dx/dt = −dV/dx+Q0.5εt, where Q is the noise variance. The model successfully mirrored the behavioral dynamics of agents in a social neurobiological system, exemplified by interactions of players in a team sport.