The Open Science agenda holds that science advances faster when we can build on existing results. Therefore, research data must be FAIR (Findable, Accessible, Interoperable, and Reusable) in order to advance the findability, reproducibility and reuse of research results. Besides the research data, all the processing steps on these data – as basis of scientific publications – have to be available, too.For good scientific practice, the resulting research software should be both open and adhere to the FAIR principles to allow full repeatability, reproducibility, and reuse. As compared to research data, research software should be both archived for reproducibility and actively maintained for reusability.The FAIR data principles do not require openness, but research software should be open source software. Established open source software licenses provide sufficient licensing options, such that it should be the rare exception to keep research software closed.We review and analyze the current state in this area in order to give recommendations for making research software FAIR and open.

To effect change, the Software Sustainability Institute works with researchers, developers, funders, and infrastructure providers to identify and address key issues with research software.Software is critical to research. A recent survey showed that 84 percent of researchers view developing software as "important or very important for their own research." [1] Despite this exalted position, little emphasis is placed on developing good software, which meets the same rigorous specifications that researchers expect of their other tools.Many researchers are yet to be convinced of the importance of developing wellengineered software. Although we might disagree with this viewpoint, it's an understandable one, because the research community provides little if any reward for producing such software. A lack of reward leads researchers to choose quick fixes over a more considered, maintainable approach to development. The effect is to burden much research software with an intractable technical debt (where work is needed to correctly engineer the quick fixes that have been implemented).Researchers who are keen to develop or incorporate software into their research also face obstacles. It's difficult to gain the necessary development skills, because training in software engineering is difficult to obtain, and it's difficult to employ already trained developers on an academic project. In 2010, the Software Sustainability Institute was founded by the UK's Engineering and Physical Sciences Research Council (the largest of the UK government's seven research funding bodies).The Software Sustainability Institute is a partnership between the universities of Edinburgh, Manchester, Oxford, and Southampton. Its goal is to cultivate worldclass research with software, by overcoming the problems that beset research software and changing the way that researchers view it. Reproducibility: A Study of ComplexityIf we're to change the way that researchers deal with software, work is required on many fronts: on software development, on the community that uses and develops software, on the training that's available, and on influencing the policy that motivates all of the stakeholders in the research software community. To understand the complexity of these problems, we need only look at the issues around reproducibility.Reproducibility is a core principle of science. As such, most researchers will have bemoaned the state of a graduate student's lab book, and argued for a clear, understandable,

The advantages and potential hazards of using a planar waveguide as the host in a high-power diode-pumped laser system are described. The techniques discussed include the use of proximity-coupled diodes, double-clad waveguides, unstable resonators, tapers, and integrated passive Q switches. Laser devices are described based on Yb3+-, Nd3+-, and Tm3+-doped YAG, and monolithic and highly compact waveguide lasers with outputs greater than 10 W are demonstrated. The prospects for scaling to the 100 W level and for further integration of devices for added functionality in a monolithic laser system are discussed.

Software is the key crosscutting technology that enables advances in mathematics, computer science, and domain-specific science and engineering to achieve robust simulations and analysis for science, engineering, and other research fields. However, software itself has not traditionally received focused attention from research communities; rather, software has evolved organically and inconsistently, with its development largely as by-products of other initiatives. Moreover, challenges in scientific software are expanding due to disruptive changes in computer hardware, increasing scale and complexity of data, and demands for more complex simulations involving multiphysics, multiscale modeling and outer-loop analysis. In recent years, community members have established a range of grass-roots organizations and projects to address these growing technical and social challenges in software productivity, quality, reproducibility, and sustainability. This article provides an overview of such groups and discusses opportunities to leverage their synergistic activities while nurturing work toward emerging software ecosystems.