Strategic alliance motivation for technology commercialization and product development

- Purpose: This paper aims to investigate the relationship among alliance motivation (AM), execution of cooperation (EC) and alliance performance of strategic alliance for commercializing technology and developing products. - Design/methodology/approach: The measurements were constructed and tested empirically through a survey of 320 strategic alliances in the food processing industry in Thailand. Confirmatory factor analysis and structural equation modelling were applied to refine scales for measuring AM, execution and cooperation performance. - Findings: This research found that firms adopted social interaction with alliance partners in order to establish mutual expectations about technology characteristics, access opportunity and organisational management styles, factors that are shown to have positive influences on both commercial and partnership performance. Findings also confirm a significant positive impact of technology characteristics, access opportunity, market potential and financial benefit on the adoption of a formal partnership agreement, but a significant impact only on commercial performance. - Research limitations/implications: Further research should use random samples in different industries in other emerging economies, and other data analysis methods to assess decision-making in strategic technology alliances that may include different types of partnerships. - Practical implications: The findings are also useful for managers who leverage operations with external resources obtained through strategic alliances parameters both in the process of managing relationships and achieving results. - Originality/value: This article contributes to extant literature by developing a practical measurement system of AM, actual EC and resulting performance in an emerging economy country. It also contributes to clarify the decision-making of firms that form strategic alliances for commercializing technology and developing products to facilitate more quality management research in other industries and countries

Six‐Axis Ground Motion Measurements of Caldera Collapse at Kīlauea Volcano, Hawai'i—More Data, More Puzzles?

Near‐field recordings of large earthquakes and volcano‐induced events using traditional seismological instrumentation often suffer from unaccounted effects of local tilt and saturation of signals. Recent hardware advances have led to the development of the blueSeis‐3A, a very broadband, highly sensitive rotational motion sensor. We installed this sensor in close proximity to permanently deployed classical instrumentation (i.e., translational seismometer, accelerometer, and tiltmeter) at the Hawaiian Volcano Observatory (USGS). There, we were able to record three ~Mw 5 earthquakes associated with large collapse events during the later phase of the 2018 Kīlauea summit eruption. Located less than 2 km from the origins of these sources, the combined six‐axis translational and rotational measurements revealed clear static rotations around all three coordinate axes. With these six component recordings, we have been able to reconstruct the complete time history of ground motion of a fixed point during an earthquake for the first time

Numerical modelling of climate change impacts on freshwater lenses on the North Sea Island of Borkum using hydrological and geophysical methods

A numerical, density dependent groundwater model is set up for the North Sea Island of Borkum to estimate climate change impacts on coastal aquifers and especially the situation of barrier islands in the Wadden Sea. The database includes information from boreholes, a seismic survey, a helicopter-borne electromagnetic (HEM) survey, monitoring of the freshwater-saltwater boundary by vertical electrode chains in two boreholes, measurements of groundwater table, pumping and slug tests, as well as water samples. Based on a statistical analysis of borehole columns, seismic sections and HEM, a hydrogeological model is set up. The groundwater model is developed using the finite-element programme FEFLOW. The density dependent groundwater model is calibrated on the basis of hydraulic, hydrological and geophysical data, in particular spatial HEM and local monitoring data. Verification runs with the calibrated model show good agreement between measured and computed hydraulic heads. A good agreement is also obtained between measured and computed density or total dissolved solids data for both the entire freshwater lens on a large scale and in the area of the well fields on a small scale. For simulating future changes in this coastal groundwater system until the end of the current century, we use the climate scenario A2, specified by the Intergovernmental Panel on Climate Change and, in particular, the data for the German North Sea coast. Simulation runs show proceeding salinisation with time beneath the well fields of the two waterworks Waterdelle and Ostland. The modelling study shows that the spreading of well fields is an appropriate protection measure against excessive salinisation of the water supply until the end of the current century

Influence of electron correlations on ground-state properties of III-V semiconductors

Lattice constants and bulk moduli of eleven cubic III-V semiconductors are calculated using an ab initio scheme. Correlation contributions of the valence electrons, in particular, are determined using increments for localized bonds and for pairs and triples of such bonds; individual increments, in turn, are evaluated using the coupled cluster approach with single and double excitations. Core-valence correlation is taken into account by means of a core polarization potential. Combining the results at the correlated level with corresponding Hartree-Fock data, we obtain lattice constants which agree with experiment within an average error of -0.2%; bulk moduli are accurate to +4%. We discuss in detail the influence of the various correlation contributions on lattice constants and bulk moduli.Comment: 4 pages, Latex, no figures, Phys. Rev. B, accepte

Banse, K. and S.A. Piontkovsky (eds.). The mesoscale structure of the epipelagic ecosystem of the open Northern Arabian Sea

Book review: BANSE, K. and S.A. PIONTKOVSKY (eds.). – 2006. The mesoscale structure of the epipelagic ecosystem of the open Northern Arabian Sea. Universities Press, Hyderabad, India. 237 pp. ISBN 81 7371 496 7This book presents an extensive body of information obtained mainly from the thirtieth cruise of the R/V Professor Bodyanitsky to the Arabian Sea, carried out in 1990. It is part of a series published by the Universities Press, India, with the support of the Indian Academy of Sciences in Bangalore, whose aim is to narrow the English-Russian language gap concerning scientific literature on low-latitude oceansPeer reviewe

Electron correlations for ground state properties of group IV semiconductors

Valence energies for crystalline C, Si, Ge, and Sn with diamond structure have been determined using an ab-initio approach based on information from cluster calculations. Correlation contributions, in particular, have been evaluated in the coupled electron pair approximation (CEPA), by means of increments obtained for localized bond orbitals and for pairs and triples of such bonds. Combining these results with corresponding Hartree-Fock (HF) data, we recover about 95 % of the experimental cohesive energies. Lattice constants are overestimated at the HF level by about 1.5 %; correlation effects reduce these deviations to values which are within the error bounds of this method. A similar behavior is found for the bulk modulus: the HF values which are significantly too high are reduced by correlation effects to about 97 % of the experimental values.Comment: 22 pages, latex, 2 figure

The geometry of nonlinear least squares with applications to sloppy models and optimization

Parameter estimation by nonlinear least squares minimization is a common problem with an elegant geometric interpretation: the possible parameter values of a model induce a manifold in the space of data predictions. The minimization problem is then to find the point on the manifold closest to the data. We show that the model manifolds of a large class of models, known as sloppy models, have many universal features; they are characterized by a geometric series of widths, extrinsic curvatures, and parameter-effects curvatures. A number of common difficulties in optimizing least squares problems are due to this common structure. First, algorithms tend to run into the boundaries of the model manifold, causing parameters to diverge or become unphysical. We introduce the model graph as an extension of the model manifold to remedy this problem. We argue that appropriate priors can remove the boundaries and improve convergence rates. We show that typical fits will have many evaporated parameters. Second, bare model parameters are usually ill-suited to describing model behavior; cost contours in parameter space tend to form hierarchies of plateaus and canyons. Geometrically, we understand this inconvenient parametrization as an extremely skewed coordinate basis and show that it induces a large parameter-effects curvature on the manifold. Using coordinates based on geodesic motion, these narrow canyons are transformed in many cases into a single quadratic, isotropic basin. We interpret the modified Gauss-Newton and Levenberg-Marquardt fitting algorithms as an Euler approximation to geodesic motion in these natural coordinates on the model manifold and the model graph respectively. By adding a geodesic acceleration adjustment to these algorithms, we alleviate the difficulties from parameter-effects curvature, improving both efficiency and success rates at finding good fits.Comment: 40 pages, 29 Figure

The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset

Purpose: To organize a knee MRI segmentation challenge for characterizing the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring osteoarthritis progression. Methods: A dataset partition consisting of 3D knee MRI from 88 subjects at two timepoints with ground-truth articular (femoral, tibial, patellar) cartilage and meniscus segmentations was standardized. Challenge submissions and a majority-vote ensemble were evaluated using Dice score, average symmetric surface distance, volumetric overlap error, and coefficient of variation on a hold-out test set. Similarities in network segmentations were evaluated using pairwise Dice correlations. Articular cartilage thickness was computed per-scan and longitudinally. Correlation between thickness error and segmentation metrics was measured using Pearson's coefficient. Two empirical upper bounds for ensemble performance were computed using combinations of model outputs that consolidated true positives and true negatives. Results: Six teams (T1-T6) submitted entries for the challenge. No significant differences were observed across all segmentation metrics for all tissues (p=1.0) among the four top-performing networks (T2, T3, T4, T6). Dice correlations between network pairs were high (>0.85). Per-scan thickness errors were negligible among T1-T4 (p=0.99) and longitudinal changes showed minimal bias (<0.03mm). Low correlations (<0.41) were observed between segmentation metrics and thickness error. The majority-vote ensemble was comparable to top performing networks (p=1.0). Empirical upper bound performances were similar for both combinations (p=1.0). Conclusion: Diverse networks learned to segment the knee similarly where high segmentation accuracy did not correlate to cartilage thickness accuracy. Voting ensembles did not outperform individual networks but may help regularize individual models.Comment: Submitted to Radiology: Artificial Intelligence; Fixed typo

Preference Articulation by Means of the R2 Indicator

International audienceIn multi-objective optimization, set-based performance indicators have become the state of the art for assessing the quality of Pareto front approximations. As a consequence, they are also more and more used within the design of multi-objective optimization algorithms. The R2 and the Hypervolume (HV) indicator represent two popular examples. In order to understand the behavior and the approximations preferred by these indicators and algorithms, a comprehensive knowledge of the indicator's properties is required. Whereas this knowledge is available for the HV, we presented a first approach in this direction for the R2 indicator just recently. In this paper, we build upon this knowledge and enhance the considerations with respect to the integration of preferences into the R2 indicator. More specifically, we analyze the effect of the reference point, the domain of the weights, and the distribution of weight vectors on the optimization of μ solutions with respect to the R2 indicator. By means of theoretical findings and empirical evidence, we show the potentials of these three possibilities using the optimal distribution of μ solutions for exemplary setups

Numerical modelling of climate change impacts on freshwater lenses on the North Sea Island of Borkum using hydrological and geophysical methods

A numerical, density dependent groundwater model is set up for the North Sea Island of Borkum to estimate climate change impacts on coastal aquifers and especially the situation of barrier islands in the Wadden Sea. The database includes information from boreholes, a seismic survey, a helicopter-borne electromagnetic (HEM) survey, monitoring of the freshwater-saltwater boundary by vertical electrode chains in two boreholes, measurements of groundwater table, pumping and slug tests, as well as water samples. Based on a statistical analysis of borehole columns, seismic sections and HEM, a hydrogeological model is set up. The groundwater model is developed using the finite-element programme FEFLOW. The density dependent groundwater model is calibrated on the basis of hydraulic, hydrological and geophysical data, in particular spatial HEM and local monitoring data. Verification runs with the calibrated model show good agreement between measured and computed hydraulic heads. A good agreement is also obtained between measured and computed density or total dissolved solids data for both the entire freshwater lens on a large scale and in the area of the well fields on a small scale. &lt;br&gt;&lt;br&gt; For simulating future changes in this coastal groundwater system until the end of the current century, we use the climate scenario A2, specified by the Intergovernmental Panel on Climate Change and, in particular, the data for the German North Sea coast. Simulation runs show proceeding salinisation with time beneath the well fields of the two waterworks Waterdelle and Ostland. &lt;br&gt;&lt;br&gt; The modelling study shows that the spreading of well fields is an appropriate protection measure against excessive salinisation of the water supply until the end of the current century