Research on proactive work behavior has been thriving. Proactive behavior involves initiating action in order to bring about positive change (Frese & Fay, 2001; Parker, Bindl, & Strauss, 2010). Several theoretical frameworks and a large body of research give insights into the antecedents of proactive behavior. With regard to the outcomes of proactive behavior, extant research has focused primarily on performance related outcomes. The effect on the well-being of individuals’ engaging in proactive behavior has so far received little attention. The few existing studies on the effect of proactive behavior on well-being suggest a complex relationship, because two contradictory findings need to be integrated. On the one hand, proactive behavior and related constructs have a high level of stability over time (Frese, Garst, & Fay, 2007; Li, Fay, Frese, Harms, & Gao, 2014). On the other hand, our own recent research suggests that proactive behavior has costs for individuals’ well-being. Proactive behavior results in elevated levels of daily cortisol output and daily fatigue (Fay & Hüttges, 2015), and is – under specific working conditions – associated with increases in job strain over longer periods of time (Strauss, Parker, & O’Shea, 2016). Together, these findings point to a contradiction that has to be resolved. If proactive behavior has costs for individuals’ well-being, why do individuals maintain their proactive behavior? To resolve this contradiction, we propose a model that does not only focus on proactive behavior’s effects on hedonic well-being, but that also incorporates eudaimonic well-being. Work psychology has only recently begun to acknowledge the relevance of eudaimonic well-being (Sonnentag, 2015). Our model proposes that while proactive behaviors may have costs in terms of hedonic well-being, there are simultaneous and longer term benefits for eudaimonic well-being. Eudaimonic well-being may compensate for the negative effects on hedonic well-being. The model spells out differential mediating pathways that help to unlock the black box between proactive behavior and well-being. Furthermore, research on proactive behavior has so far barely taken the national culture as the context in which proactive behavior emerges into account. Culture and its associated values, expectations, and behavioral norms are likely to affect the proactivity – well-being relationship. Because of its change oriented nature, proactive behavior is likely to be particularly taxing in countries with elevated levels of uncertainty avoidance. A comparison between France and Germany lends itself to a cultural comparison, because France and Germany differ substantially in their level of uncertainty avoidance (Chhokar, et al., 2007). The present proposal includes three studies. They are designed to test for short-, mid- and long-term effects, taking the proposed mediating variables into account. All studies include a cross-cultural comparison.

Optical microscopy is the most widely used imaging tool in laboratories all around the world. Indeed, According to BCC market research, the global optical microscopy market will be worth US$6.3 billion in 2020. Several Nobel prizes have been awarded for contributions made to the development of optical microscopy, including most recently in 2014. There is, however, a major limitation facing optical microscopy: it is difficult, if not impossible, to image tissue hidden beneath layers of overlying tissue. This occurs for the same reason that it is difficult to see clearly through a window covered in rain drops - tissue is highly scattering, like rain drops, and critically degrades image quality. This is important as it prevents in-tact tissue from being imaged in its natural environment, requiring tissue to instead be sliced into thin sections. A variety of approaches have been used in an attempt to overcome this problem. All such approaches are generally similar in that they insert hardware into the microscope in an attempt to compensate for the degradation due to the sample. This is similar to humans using spectacles to overcome imperfections of their eye. The main difference is that opticians are able to precisely determine the imperfections that each eye has, and thus design spectacles which perfectly compensate for them. No such method has been developed for measuring sample induced imperfections, or aberrations, present in microscope images. This project proposes to do just that: measure the imperfections caused by the sample itself. This will be achieved by computing the optical structure of the sample (i.e., how light travels in the sample) via a two stage process. Firstly, the sample will be imaged by a microscope capable of performing rapid three-dimensional imaging called an optical coherence microscope (OCM). OCM works very much like ultrasound imaging, except light is used instead of sound waves. The second step involves developing a sophisticated computational procedure for calculating the sample's optical structure from the OCM image. This will be performed using a recently mathematical model, developed recently by the project team, which allows OCM images to be predicted from a given sample structure. Clearly, our task is to solve the opposite problem: calculate the sample's structure given a measured OCM image. Formal techniques have been established for solving the problem in the opposite fashion which will be adapted specifically for this project. Once the sample's optical structure has been solved, in a follow-on project, existing methods will be employed for restoring optical fluorescence microscope images which have been degraded by the sample itself. This will enable fluorescence microscopy to be performed at depths within tissue which are currently inaccessible. This will be highly advantageous to many biological researchers in the UK and the world.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

The "smell of the seaside" is actually caused by a gaseous compound called dimethyl sulfide (DMS) that is produced by microbes. This gas is important because it is a very abundant organic sulfur compound which is released to the air from the marine environment. Globally, approximately 300 million tons of DMS per annum is produced, mainly by bacteria. Also, chemical products arising from DMS oxidation help form clouds over the oceans, to an extent that affects the sunlight reaching the Earth's surface, with effects on climate. In turn, these products are delivered back to Earth as rain, representing a key component of the global sulfur cycle. Interestingly, DMS is a potent chemo-attractant for many organisms including seabirds, crustaceans and marine mammals that all move towards DMS because they associate DMS with food. Currently it is widely accepted that DMS is mainly produced as a result of microbes degrading the osmolyte dimethylsulfoniopropionate (DMSP), which is produced by phytoplankton in the oceans, by seaweeds and by a few salt-tolerant plants. Our preliminary work and that of Ron Kiene, has prompted us to question whether it is solely these processes that produce DMS. In our preliminary data we have: 1. Found a microbial pathway, the methanethiol-dependent DMS production (Mdd) pathway, that produces DMS but which does not involve DMSP. 2. Shown how the bacterium "Pseudomonas deceptionensis" makes DMS via a gene called mddA. 3. Shown that this gene is found in a wide range of bacteria such as Bradyrhizobium japonicum, a nitrogen-fixing symbiont of soybeans, Mycobacterium tuberculosis, the causative agent of tuberculosis and some cyanobacteria. 4. Shown that the Mdd pathway is active in both salty and freshwater sediments and that the mddA gene is abundant in bacteria living in marine sediments. 5. Shown that other bacteria have other undiscovered ways of making DMS from methanethiol. We wish to investigate how important this novel DMS production pathway is for the global production of this climate changing gas. To answer this question, we will sample various marine and freshwater environments and investigate how active the Mdd pathway is in these environments and how this novel pathway for the production of DMS is regulated. We already know that this Mdd pathway is probably active in most of our sample sites, which include mud from a saltmarsh, a freshwater lake, a peat bog and seawater. It is equally important to know which microbes are responsible for the process (mediated by Mdd) and why they produce DMS. We will use a powerful suite of microbial ecology techniques, combined with genetic tools to identify the microbes and the key genes involved in producing DMS via this new Mdd pathway. We will identify: a) the microbes living in both the oxic and anoxic mud samples and in seawater; b) how these microbial communities change when we enrich for increased DMS production via the Mdd pathway and c) which forms of the mddA gene (and the enzyme encoded by this gene) are responsible for high DMS production in these varied environments. To understand how and why bacteria in the environment are Mdd active, we will study in detail a few model bacteria, some of which have been isolated from our sample sites. This will involve identifying and mutating the genes encoding the Mdd pathway to ascertain why they use it. This will be done with bacteria that have a specific gene "mddA", but, also on those that do not, which will allow us to identify new mdd genes. Given the environmental consequences of the climate-active gas DMS, it is important to know which types of microbes affect its production and which of the various potential pathways are involved. This will help us in the future to model how changes in the environment impact on the balance of these climate processes.

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