273 research outputs found
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The temporary marketing organization
Increasingly, marketing activity is carried out within temporary organizations, where teams are assembled to complete a specific task within a predetermined timeframe. Such organizations are uniquely suited to promoting various marketing outcomes but are not well understood. From a practical standpoint, their inherent characteristics create organizational challenges which, if not appropriately managed, can compromise performance. Drawing on agency theory and research on embedded ties, we conceptualize these challenges in terms of particular selection and enforcement problems. We identify three different forms of temporary marketing organizations that vary in their selection and enforcement qualities. Next, we develop a conceptual framework which shows the selection and enforcement implications of a temporary organization’s task, timeline and team composition. We also show how selection and enforcement mechanisms have portable qualities and can be “imported” to a given temporary organization, either from a prior temporary organization or from a larger permanent one
Positive Feedbacks in Seagrass Ecosystems – Evidence from Large-Scale Empirical Data
Positive feedbacks cause a nonlinear response of ecosystems to environmental change and may even cause bistability. Even though the importance of feedback mechanisms has been demonstrated for many types of ecosystems, their identification and quantification is still difficult. Here, we investigated whether positive feedbacks between seagrasses and light conditions are likely in seagrass ecosystems dominated by the temperate seagrass Zostera marina. We applied a combination of multiple linear regression and structural equation modeling (SEM) on a dataset containing 83 sites scattered across Western Europe. Results confirmed that a positive feedback between sediment conditions, light conditions and seagrass density is likely to exist in seagrass ecosystems. This feedback indicated that seagrasses are able to trap and stabilize suspended sediments, which in turn improves water clarity and seagrass growth conditions. Furthermore, our analyses demonstrated that effects of eutrophication on light conditions, as indicated by surface water total nitrogen, were on average at least as important as sediment conditions. This suggests that in general, eutrophication might be the most important factor controlling seagrasses in sheltered estuaries, while the seagrass-sediment-light feedback is a dominant mechanism in more exposed areas. Our study demonstrates the potentials of SEM to identify and quantify positive feedbacks mechanisms for ecosystems and other complex systems
Positive Feedbacks in Seagrass Ecosystems – Evidence from Large-Scale Empirical Data
Positive feedbacks cause a nonlinear response of ecosystems to environmental change and may even cause bistability. Even though the importance of feedback mechanisms has been demonstrated for many types of ecosystems, their identification and quantification is still difficult. Here, we investigated whether positive feedbacks between seagrasses and light conditions are likely in seagrass ecosystems dominated by the temperate seagrass Zostera marina. We applied a combination of multiple linear regression and structural equation modeling (SEM) on a dataset containing 83 sites scattered across Western Europe. Results confirmed that a positive feedback between sediment conditions, light conditions and seagrass density is likely to exist in seagrass ecosystems. This feedback indicated that seagrasses are able to trap and stabilize suspended sediments, which in turn improves water clarity and seagrass growth conditions. Furthermore, our analyses demonstrated that effects of eutrophication on light conditions, as indicated by surface water total nitrogen, were on average at least as important as sediment conditions. This suggests that in general, eutrophication might be the most important factor controlling seagrasses in sheltered estuaries, while the seagrass-sediment-light feedback is a dominant mechanism in more exposed areas. Our study demonstrates the potentials of SEM to identify and quantify positive feedbacks mechanisms for ecosystems and other complex systems
TOMOBFLOW: feature-preserving noise filtering for electron tomography
<p>Abstract</p> <p>Background</p> <p>Noise filtering techniques are needed in electron tomography to allow proper interpretation of datasets. The standard linear filtering techniques are characterized by a tradeoff between the amount of reduced noise and the blurring of the features of interest. On the other hand, sophisticated anisotropic nonlinear filtering techniques allow noise reduction with good preservation of structures. However, these techniques are computationally intensive and are difficult to be tuned to the problem at hand.</p> <p>Results</p> <p>TOMOBFLOW is a program for noise filtering with capabilities of preservation of biologically relevant information. It is an efficient implementation of the Beltrami flow, a nonlinear filtering method that locally tunes the strength of the smoothing according to an edge indicator based on geometry properties. The fact that this method does not have free parameters hard to be tuned makes TOMOBFLOW a user-friendly filtering program equipped with the power of diffusion-based filtering methods. Furthermore, TOMOBFLOW is provided with abilities to deal with different types and formats of images in order to make it useful for electron tomography in particular and bioimaging in general.</p> <p>Conclusion</p> <p>TOMOBFLOW allows efficient noise filtering of bioimaging datasets with preservation of the features of interest, thereby yielding data better suited for post-processing, visualization and interpretation. It is available at the web site <url>http://www.ual.es/%7ejjfdez/SW/tomobflow.html</url>.</p
How managers can build trust in strategic alliances: a meta-analysis on the central trust-building mechanisms
Trust is an important driver of superior alliance performance. Alliance managers are influential in this regard because trust requires active involvement, commitment and the dedicated support of the key actors involved in the strategic alliance. Despite the importance of trust for explaining alliance performance, little effort has been made to systematically investigate the mechanisms that managers can use to purposefully create trust in strategic alliances. We use Parkhe’s (1998b) theoretical framework to derive nine hypotheses that distinguish between process-based, characteristic-based and institutional-based trust-building mechanisms. Our meta-analysis of 64 empirical studies shows that trust is strongly related to alliance performance. Process-based mechanisms are more important for building trust than characteristic- and institutional-based mechanisms. The effects of prior ties and asset specificity are not as strong as expected and the impact of safeguards on trust is not well understood. Overall, theoretical trust research has outpaced empirical research by far and promising opportunities for future empirical research exist
No improvement in long-term wear and revision rates with the second-generation Biomet cup (RingLoc) in young patients: 141 hips followed for median 12 years
Optimising joint reconstruction management in arthritis and bone tumour patient
Coordinated optimization of visual cortical maps (I) Symmetry-based analysis
In the primary visual cortex of primates and carnivores, functional
architecture can be characterized by maps of various stimulus features such as
orientation preference (OP), ocular dominance (OD), and spatial frequency. It
is a long-standing question in theoretical neuroscience whether the observed
maps should be interpreted as optima of a specific energy functional that
summarizes the design principles of cortical functional architecture. A
rigorous evaluation of this optimization hypothesis is particularly demanded by
recent evidence that the functional architecture of OP columns precisely
follows species invariant quantitative laws. Because it would be desirable to
infer the form of such an optimization principle from the biological data, the
optimization approach to explain cortical functional architecture raises the
following questions: i) What are the genuine ground states of candidate energy
functionals and how can they be calculated with precision and rigor? ii) How do
differences in candidate optimization principles impact on the predicted map
structure and conversely what can be learned about an hypothetical underlying
optimization principle from observations on map structure? iii) Is there a way
to analyze the coordinated organization of cortical maps predicted by
optimization principles in general? To answer these questions we developed a
general dynamical systems approach to the combined optimization of visual
cortical maps of OP and another scalar feature such as OD or spatial frequency
preference.Comment: 90 pages, 16 figure
Coordinated optimization of visual cortical maps (II) Numerical studies
It is an attractive hypothesis that the spatial structure of visual cortical
architecture can be explained by the coordinated optimization of multiple
visual cortical maps representing orientation preference (OP), ocular dominance
(OD), spatial frequency, or direction preference. In part (I) of this study we
defined a class of analytically tractable coordinated optimization models and
solved representative examples in which a spatially complex organization of the
orientation preference map is induced by inter-map interactions. We found that
attractor solutions near symmetry breaking threshold predict a highly ordered
map layout and require a substantial OD bias for OP pinwheel stabilization.
Here we examine in numerical simulations whether such models exhibit
biologically more realistic spatially irregular solutions at a finite distance
from threshold and when transients towards attractor states are considered. We
also examine whether model behavior qualitatively changes when the spatial
periodicities of the two maps are detuned and when considering more than 2
feature dimensions. Our numerical results support the view that neither minimal
energy states nor intermediate transient states of our coordinated optimization
models successfully explain the spatially irregular architecture of the visual
cortex. We discuss several alternative scenarios and additional factors that
may improve the agreement between model solutions and biological observations.Comment: 55 pages, 11 figures. arXiv admin note: substantial text overlap with
arXiv:1102.335
Evidence for 'critical slowing down' in seagrass:a stress gradient experiment at the southern limit of its range
The theory of critical slowing down, i.e. the increasing recovery times of complex systems close to tipping points, has been proposed as an early warning signal for collapse. Empirical evidence for the reality of such warning signals is still rare in ecology. We studied this on Zostera noltii intertidal seagrass meadows at their southern range limit, the Banc d'Arguin, Mauritania. We analyse the environmental covariates of recovery rates using structural equation modelling (SEM), based on an experiment in which we assessed whether recovery after disturbances (i.e. seagrass & infauna removal) depends on stress intensity (increasing with elevation) and disturbance patch size (1 m(2) vs. 9 m(2)). The SEM analyses revealed that higher biofilm density and sediment accretion best explained seagrass recovery rates. Experimental disturbances were followed by slow rates of recovery, regrowth occurring mainly in the coolest months of the year. Macrofauna recolonisation lagged behind seagrass recovery. Overall, the recovery rate was six times slower in the high intertidal zone than in the low zone. The large disturbances in the low zone recovered faster than the small ones in the high zone. This provides empirical evidence for critical slowing down with increasing desiccation stress in an intertidal seagrass system
Protein Profile Changes during Porcine Oocyte Aging and Effects of Caffeine on Protein Expression Patterns
It has been shown that oocyte aging critically affects reproduction and development. By using proteomic tools, in the present study, changes in protein profiles during porcine oocyte aging and effects of caffeine on oocyte aging were investigated. By comparing control MII oocytes with aging MII oocytes, we identified 23 proteins that were up-regulated and 3 proteins that were down-regulated during the aging process. In caffeine-treated oocytes, 6 proteins were identified as up-regulated and 12 proteins were identified as down-regulated. A total of 38 differentially expressed proteins grouped into 5 regulation patterns were determined to relate to the aging and anti-aging process. By using the Gene Ontology system, we found that numerous functional gene products involved in metabolism, stress response, reactive oxygen species and cell cycle regulation were differentially expressed during the oocyte aging process, and most of these proteins are for the first time reported in our study, including 2 novel proteins. In addition, several proteins were found to be modified during oocyte aging. These data contribute new information that may be useful for future research on cellular aging and for improvement of oocyte quality
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