Obsessed With Work: A multi-causal and multi-rater approach to workaholism

Workaholism is defined as the combination of two underlying dimensions: working excessively and working compulsively. The present thesis aims at achieving the following purposes: 1) to test whether the interaction between environmental and personal antecedents may enhance workaholism; 2) to develop a questionnaire aimed to assess overwork climate in the workplace; 3) to contrast focal employees’ and coworkers’ perceptions of employees’ workaholism and engagement. Concerning the first purpose, the interaction between overwork climate and person characteristics (achievement motivation, perfectionism, conscientiousness, self-efficacy) was explored on a sample of 333 Dutch employees. The results of moderated regression analyses showed that the interaction between overwork climate and person characteristics is related to workaholism. The second purpose was pursued with two interrelated studies. In Study 1 the Overwork Climate Scale (OWCS) was developed and tested using a principal component analysis (N = 395) and a confirmatory factor analysis (N = 396). Two overwork climate dimensions were distinguished, overwork endorsement and lacking overwork rewards. In Study 2 the total sample (N = 791) was used to explore the association of overwork climate with two types of working hard: work engagement and workaholism. Lacking overwork rewards was negatively associated with engagement, whereas overwork endorsement showed a positive association with workaholism. Concerning the third purpose, using a sample of 73 dyads composed by focal employees and their coworkers, a multitrait-multimethod matrix and a correlated trait-correlated method model, i.e. the CT-C(M–1) model, were examined. Our results showed a considerable agreement between raters on focal employees' engagement and workaholism. In contrast, we observed a significant difference concerning the cognitive dimension of workaholism, working compulsively. Moreover, we provided further evidence for the discriminant validity between engagement and workaholism. Overall, workaholism appears as a negative work-related state that could be better explained by assuming a multi-causal and multi-rater approach.

Groupme: city data and multi-preference activity allocation

Classic group recommender systems focus on providing suggestions for a fixed group of people. Our work tries to give an inside look at design- ing a new recommender system that is capable of making suggestions for a sequence of activities, dividing people in subgroups, in order to boost over- all group satisfaction. However, this idea increases problem complexity in more dimensions and creates great challenge to the algorithm’s performance. To understand the e↵ectiveness, due to the enhanced complexity and pre- cise problem solving, we implemented an experimental system from data collected from a variety of web services concerning the city of Paris. The sys- tem recommends activities to a group of users from two di↵erent approaches: Local Search and Constraint Programming. The general results show that the number of subgroups can significantly influence the Constraint Program- ming Approaches’s computational time and e�cacy. Generally, Local Search can find results much quicker than Constraint Programming. Over a lengthy period of time, Local Search performs better than Constraint Programming, with similar final results.

Coupling biomechanics to a cellular level model: An approach to patient-specific image driven multi-scale and multi-physics tumor simulation

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20\% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning.

Diesel spray mixing limited vaporization with non-ideal and multi-component fuel thermophysical property effects

Internal combustion engines are, and will continue to be, a primary mode of power generation for ground transportation. Challenges exist in meeting fuel consumption regulations and emission standards while upholding performance, as fuel prices rise, and resource depletion and environmental impacts are of increasing concern. Diesel engines are advantageous due to their inherent efficiency advantage over spark ignition engines; however, their NOx and soot emissions can be difficult to control and reduce due to an inherent tradeoff. Diesel combustion is spray and mixing controlled providing an intrinsic link between spray and emissions, motivating detailed, fundamental studies on spray, vaporization, mixing, and combustion characteristics under engine relevant conditions. An optical combustion vessel facility has been developed at Michigan Technological University for these studies, with detailed tests and analysis being conducted. In this combustion vessel facility a preburn procedure for thermodynamic state generation is used, and validated using chemical kinetics modeling both for the MTU vessel, and institutions comprising the Engine Combustion Network international collaborative research initiative. It is shown that minor species produced are representative of modern diesel engines running exhaust gas recirculation and do not impact the autoignition of n-heptane. Diesel spray testing of a high-pressure (2000 bar) multi-hole injector is undertaken including non-vaporizing, vaporizing, and combusting tests, with sprays characterized using Mie back scatter imaging diagnostics. Liquid phase spray parameter trends agree with literature. Fluctuations in liquid length about a quasi-steady value are quantified, along with plume to plume variations. Hypotheses are developed for their causes including fuel pressure fluctuations, nozzle cavitation, internal injector flow and geometry, chamber temperature gradients, and turbulence. These are explored using a mixing limited vaporization model with an equation of state approach for thermopyhysical properties. This model is also applied to single and multi-component surrogates. Results include the development of the combustion research facility and validated thermodynamic state generation procedure. The developed equation of state approach provides application for improving surrogate fuels, both single and multi-component, in terms of diesel spray liquid length, with knowledge of only critical fuel properties. Experimental studies are coupled with modeling incorporating improved thermodynamic non-ideal gas and fuel

Registration of Sub-Sequence and Multi-Camera Reconstructions for Camera Motion Estimation

This paper presents different application scenarios for which the registration of sub-sequence reconstructions or multi-camera reconstructions is essential for successful camera motion estimation and 3D reconstruction from video. The registration is achieved by merging unconnected feature point tracks between the reconstructions. One application is drift removal for sequential camera motion estimation of long sequences. The state-of-the-art in drift removal is to apply a RANSAC approach to find unconnected feature point tracks. In this paper an alternative spectral algorithm for pairwise matching of unconnected feature point tracks is used. It is then shown that the algorithms can be combined and applied to novel scenarios where independent camera motion estimations must be registered into a common global coordinate system. In the first scenario multiple moving cameras, which capture the same scene simultaneously, are registered. A second new scenario occurs in situations where the tracking of feature points during sequential camera motion estimation fails completely, e.g., due to large occluding objects in the foreground, and the unconnected tracks of the independent reconstructions must be merged. In the third scenario image sequences of the same scene, which are captured under different illuminations, are registered. Several experiments with challenging real video sequences demonstrate that the presented techniques work in practice.

The performance of single- and multi-proxy transfer functions (testate amoebae, bryophytes, vascular plants) for reconstructing mire surface wetness and pH

Peatlands are widely exploited archives of paleoenvironmental change. We developed and compared multiple transfer functions to infer peatland depth to the water table (DWT) and pH based on testate amoeba (percentages, or presence/absence), bryophyte presence/absence, and vascular plant presence/absence data from sub-alpine peatlands in the SE Swiss Alps in order to 1) compare the performance of single-proxy vs. multi-proxy models and 2) assess the performance of presence/absence models. Bootstrapping cross-validation showing the best performing single-proxy transfer functions for both DWT and pH were those based on bryophytes. The best performing transfer functions overall for DWT were those based on combined testate amoebae percentages, bryophytes and vascular plants; and, for pH, those based on testate amoebae and bryophytes. The comparison of DWT and pH inferred from testate amoeba percentages and presence/absence data showed similar general patterns but differences in the magnitude and timing of some shifts. These results show new directions for paleoenvironmental research, 1) suggesting that it is possible to build good-performing transfer functions using presence/absence data, although with some loss of accuracy, and 2) supporting the idea that multi-proxy inference models may improve paleoecological reconstruction. The performance of multi-proxy and single-proxy transfer functions should be further compared in paleoecological data.

Merger decisions and executive stock ownership in acquiring firms

This study supports the proposition that managerial welfare affects merger decisions. The abnormal stock returns experienced by bidder firms, from the time of the announcement of a merger bid through the stockholder approval date, are positively relaterd to the percentage of own-company stock held by the senior management of the bidder. The results suggest that substantial amounts of own-company share ownership help align the interests of stockholders and management.