416 resultados para STRUCTURAL INFORMATION
Resumo:
We explored whether teams develop shared perceptions regarding the quantity and quality of information and the extent of participation in decision making provided in an environment of continuous change. In addition, we examined whether change climate strength moderated relationships between change climate level and team outcomes. We examined relationships among aggregated change information and change participation and aggregated team outcomes, including two role stressors (i.e., role ambiguity and role overload) and two indicators of well-being (i.e., quality of worklife and distress). Questionnaires were distributed in an Australian law enforcement agency and data were used from 178 teams. Structural equation modelling analyses, controlling for a marker variable, were conducted to examine the main effects of aggregated change information and aggregated change participation on aggregated team outcomes. Results provided support for a model that included method effects due to a marker variable. In this model, change information climate was significantly negatively associated with role ambiguity, role overload, and distress, and significantly positively associated with quality of worklife. Change participation climate was significantly positively associated with quality of worklife. Change climate strength did not moderate relationships among change climate level and team outcomes.
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Commodity price modeling is normally approached in terms of structural time-series models, in which the different components (states) have a financial interpretation. The parameters of these models can be estimated using maximum likelihood. This approach results in a non-linear parameter estimation problem and thus a key issue is how to obtain reliable initial estimates. In this paper, we focus on the initial parameter estimation problem for the Schwartz-Smith two-factor model commonly used in asset valuation. We propose the use of a two-step method. The first step considers a univariate model based only on the spot price and uses a transfer function model to obtain initial estimates of the fundamental parameters. The second step uses the estimates obtained in the first step to initialize a re-parameterized state-space-innovations based estimator, which includes information related to future prices. The second step refines the estimates obtained in the first step and also gives estimates of the remaining parameters in the model. This paper is part tutorial in nature and gives an introduction to aspects of commodity price modeling and the associated parameter estimation problem.
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Objects in an environment are often encountered sequentially during spatial learning, forming a path along which object locations are experienced. The present study investigated the effect of spatial information conveyed through the path in visual and proprioceptive learning of a room-sized spatial layout, exploring whether different modalities differentially depend on the integrity of the path. Learning object locations along a coherent path was compared with learning them in a spatially random manner. Path integrity had little effect on visual learning, whereas learning with the coherent path produced better memory performance than random order learning for proprioceptive learning. These results suggest that path information has differential effects in visual and proprioceptive spatial learning, perhaps due to a difference in the way one establishes a reference frame for representing relative locations of objects.
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During the early design stages of construction projects, accurate and timely cost feedback is critical to design decision making. This is particularly challenging for cost estimators, as they must quickly and accurately estimate the cost of the building when the design is still incomplete and evolving. State-of-the-art software tools typically use a rule-based approach to generate detailed quantities from the design details present in a building model and relate them to the cost items in a cost estimating database. In this paper, we propose a generic approach for creating and maintaining a cost estimate using flexible mappings between a building model and a cost estimate. The approach uses queries on the building design that are used to populate views, and each view is then associated with one or more cost items. The benefit of this approach is that the flexibility of modern query languages allows the estimator to encode a broad variety of relationships between the design and estimate. It also avoids the use of a common standard to which both designers and estimators must conform, allowing the estimator added flexibility and functionality to their work.
Resumo:
The strain data acquired from structural health monitoring (SHM) systems play an important role in the state monitoring and damage identification of bridges. Due to the environmental complexity of civil structures, a better understanding of the actual strain data will help filling the gap between theoretical/laboratorial results and practical application. In the study, the multi-scale features of strain response are first revealed after abundant investigations on the actual data from two typical long-span bridges. Results show that, strain types at the three typical temporal scales of 10^5, 10^2 and 10^0 sec are caused by temperature change, trains and heavy trucks, and have their respective cut-off frequency in the order of 10^-2, 10^-1 and 10^0 Hz. Multi-resolution analysis and wavelet shrinkage are applied for separating and extracting these strain types. During the above process, two methods for determining thresholds are introduced. The excellent ability of wavelet transform on simultaneously time-frequency analysis leads to an effective information extraction. After extraction, the strain data will be compressed at an attractive ratio. This research may contribute to a further understanding of actual strain data of long-span bridges; also, the proposed extracting methodology is applicable on actual SHM systems.
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Based on an investigation of 106 projects involving the use of building information modelling (BIM), this paper examines current BIM practices in China, and assesses how various practices alter their effectiveness. The results reveal that in current practice BIM is principally employed as a visualization tool, and how it is implemented is significantly associated with project characteristics. BIM use in the majority of the surveyed projects is seen to have positive outcomes, with the benefits of improved task effectiveness being more substantial than those related to efficiency improvement. The results also provide evidence that project characteristics significantly influence the success of BIM use; however, more substantial contributing factors to BIM effectiveness are the extent of integrated use and client/owner support. While indicating that current BIM practices involve both technological and organizational problems, the findings also provide insights into how the potential for BIM could be better exploited within the industry.
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A sound understanding of travellers’ behavioural changes and adaptation when facing a natural disaster is a key factor in efficiently and effectively managing transport networks at such times. This study specifically investigates the importance of travel/traffic information and its impact on travel behaviour during natural disasters. Using the 2011 Brisbane flood as a case study, survey respondents’ perceptions of the importance of travel/traffic information before, during, and after the flood were modelled using random-effects ordered logit. A hysteresis phenomenon was observed: respondents’ perceptions of the importance of travel/traffic information increased during the flood, and although its perceived importance decreased after the flood, it did not return to the pre-flood level. Results also reveal that socio-demographic features (such as gender and age) have a significant impact on respondents’ perceptions of the importance of travel/traffic information. The roles of travel time and safety in a respondent’s trip planning are also significantly correlated to their perception of the importance of this information. The analysis further shows that during the flood, respondents generally thought that travel/traffic information was important, and adjusted their travel plans according to information received. When controlling for other factors, the estimated odds of changing routes and cancelling trips for a respondent who thought that travel/traffic information was important, are respectively about three times and seven times the estimated odds for a respondent who thought that travel/traffic information was not important. In contrast, after the flood, the influence of travel/traffic information on respondents’ travel behaviour diminishes. Finally, the analysis shows no evidence of the influence of travel/traffic information’s on respondents’ travel mode; this indicates that inducing travel mode change is a challenging task.
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The DeLone and McLean (D&M) model (2003) has been broadly used and generally recognised as a useful model for gauging the success of IS implementations. However, it is not without limitations. In this study, we evaluate a model that extends the D&M model and attempts to address some of it slimitations by providing a more complete measurement model of systems success. To that end, we augment the D&M (2003) model and include three variables: business value, institutional trust, and future readiness. We propose that the addition of these variables allows systems success to be assessed at both the systems level and the business level. Consequently, we develop a measurement model rather than a structural or predictive model of systems success.
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Introduction. Social media is becoming a vital source of information in disaster or emergency situations. While a growing number of studies have explored the use of social media in natural disasters by emergency staff, military personnel, medial and other professionals, very few studies have investigated the use of social media by members of the public. The purpose of this paper is to explore citizens’ information experiences in social media during times of natural disaster. Method. A qualitative research approach was applied. Data was collected via in-depth interviews. Twenty-five people who used social media during a natural disaster in Australia participated in the study. Analysis. Audio recordings of interviews and interview transcripts provided the empirical material for data analysis. Data was analysed using structural and focussed coding methods. Results. Eight key themes depicting various aspects of participants’ information experience during a natural disaster were uncovered by the study: connected; wellbeing; coping; help; brokerage; journalism; supplementary and characteristics. Conclusion. This study contributes insights into social media’s potential for developing community disaster resilience and promotes discussion about the value of civic participation in social media when such circumstances occur. These findings also contribute to our understanding of information experiences as a new informational research object.
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Layered materials exhibit intriguing electronic characteristics and the search for new types of two-dimensional (2D) structures is of importance for future device fabrication. Using state-of-art first principle calculations, we identify and characterize the structural and electronic properties of two 2D layered arsenic materials, namely, arsenic and its alloy AsSb. The stable 2D structural configuration of arsenic is confirmed to be the low-buckled two-dimensional hexagonal structure by phonon and binding energy calculations. The monolayer exhibits indirect semiconducting properties with gap around 1.5 eV (corrected to 2.2 eV by hybrid function), which can be modulated into a direct semiconductor within a small amount of tensile strain. These semiconducting properties are preserved when cutting into 1D nanoribbons, but the band gap is edge dependent. It is interesting to find that an indirect to direct gap transition can be achieved under strain modulation of the armchair ribbon. Essentially the same phenomena can be found in layered AsSb, except a weak Rashba induced band splitting is present in AsSb due to the nonsymmetric structure and spin orbit coupling. When an additional layer is added on the top, a semiconductor–metal transition will occur. The findings here broaden the family of 2D materials beyond graphene and transition metal dichalcogenides and provide useful information for experimental fabrication of new layered materials with possible application in optoelectronics.
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CoMFA and CoMSIA analysis were utilized in this investigation to define the important interacting regions in paclitaxel/tubulin binding site and to develop selective paclitaxel-like active compounds. The starting geometry of paclitaxel analogs was taken from the crystal structure of docetaxel. A total of 28 derivatives of paclitaxel were divided into two groups—a training set comprising of 19 compounds and a test set comprising of nine compounds. They were constructed and geometrically optimized using SYBYL v6.6. CoMFA studies provided a good predictability (q2 = 0.699, r2 = 0.991, PC = 6, S.E.E. = 0.343 and F = 185.910). They showed the steric and electrostatic properties as the major interacting forces whilst the lipophilic property contribution was a minor factor for recognition forces of the binding site. These results were in agreement with the experimental data of the binding activities of these compounds. Five fields in CoMSIA analysis (steric, electrostatic, hydrophobic, hydrogen-bond acceptor and donor properties) were considered contributors in the ligand–receptor interactions. The results obtained from the CoMSIA studies were: q2 = 0.535, r2 = 0.983, PC = 5, S.E.E. = 0.452 and F = 127.884. The data obtained from both CoMFA and CoMSIA studies were interpreted with respect to the paclitaxel/tubulin binding site. This intuitively suggested where the most significant anchoring points for binding affinity are located. This information could be used for the development of new compounds having paclitaxel-like activity with new chemical entities to overcome the existing pharmaceutical barriers and the economical problem associated with the synthesis of the paclitaxel analogs. These will boost the wide use of this useful class of compounds, i.e. in brain tumors as the most of the present active compounds have poor blood–brain barrier crossing ratios and also, various tubulin isotypes has shown resistance to taxanes and other antimitotic agents.
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This paper investigates the influence of structural sealant joints on the blast performance of laminated glass (LG) panels, using a comprehensive numerical procedure. A parametric study was carried out by varying the width, thickness and the Young’s modulus (E) of the structural silicone sealant joints and the behavior of the LG panel was studied under two different blast loads. Results show that these parameters influence the blast response of LG panels, especially under the higher blast load. Sealant joints that are thicker, have smaller widths and lower E values increase the flexibility at the supports and hence increase the energy absorption of the LG panel while reducing the support reactions. Results also confirmed that sealant joints designed according to current standards perform well under blast loads. Modeling techniques presented in this paper could be used to complement and supplement the guidance in existing design standards. The new information generated in this paper will contribute towards safer and more economical designs of entire facade systems including window glazing, frames and supporting structures.
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Background Although there are many structural neuroimaging studies of attention-deficit/hyperactivity disorder (ADHD) in children, there are inconsistencies across studies and no consensus regarding which brain regions show the most robust area or volumetric reductions relative to control subjects. Our goal was to statistically analyze structural imaging data via a meta-analysis to help resolve these issues. Methods We searched the MEDLINE and PsycINFO databases through January 2005. Studies must have been written in English, used magnetic resonance imaging, and presented the means and standard deviations of regions assessed. Data were extracted by one of the authors and verified independently by another author. Results Analyses were performed using STATA with metan, metabias, and metainf programs. A meta-analysis including all regions across all studies indicated global reductions for ADHD subjects compared with control subjects, standardized mean difference equal to .408, p less than .001. Regions most frequently assessed and showing the largest differences included cerebellar regions, the splenium of the corpus callosum, total and right cerebral volume, and right caudate. Several frontal regions assessed in only two studies also showed large significant differences. Conclusions This meta-analysis provides a quantitative analysis of neuroanatomical abnormalities in ADHD and information that can be used to guide future studies.
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Structural equation modeling (SEM) is a powerful statistical approach for the testing of networks of direct and indirect theoretical causal relationships in complex data sets with intercorrelated dependent and independent variables. SEM is commonly applied in ecology, but the spatial information commonly found in ecological data remains difficult to model in a SEM framework. Here we propose a simple method for spatially explicit SEM (SE-SEM) based on the analysis of variance/covariance matrices calculated across a range of lag distances. This method provides readily interpretable plots of the change in path coefficients across scale and can be implemented using any standard SEM software package. We demonstrate the application of this method using three studies examining the relationships between environmental factors, plant community structure, nitrogen fixation, and plant competition. By design, these data sets had a spatial component, but were previously analyzed using standard SEM models. Using these data sets, we demonstrate the application of SE-SEM to regularly spaced, irregularly spaced, and ad hoc spatial sampling designs and discuss the increased inferential capability of this approach compared with standard SEM. We provide an R package, sesem, to easily implement spatial structural equation modeling.
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HIV risk in vulnerable groups such as itinerant male street labourers is often examined via a focus on individual determinants. This study provides a test of a modified Information-Motivation-Behavioral Skills (IMB) model to predict condom use behaviour among male street workers in urban Vietnam. In a cross-sectional survey using a social mapping technique, 450 male street labourers from 13 districts of Hanoi, Vietnam were recruited and interviewed. Collected data were first examined for completeness; structural equation modelling was then employed to test the model fit. Condoms were used inconsistently by many of these men, and usage varied in relation to a number of factors. A modified IMB model had a better fit than the original IMB model in predicting condom use behaviour. This modified model accounted for 49% of the variance, versus 10% by the original version. In the modified model, the influence of psychosocial factors was moderately high, whilst the influence of HIV prevention information, motivation and perceived behavioural skills was moderately low, explaining in part the limited level of condom use behaviour. This study provides insights into social factors that should be taken into account in public health planning to promote safer sexual behaviour among Asian male street labourers.