In this essay we propose a reframing of the Bloomberg Terminal, an interface used to track financial trades and values, by using it as a creative, critical and curatorial device to explore the relationship between the art and finance. To contextualise this approach, we offer a history of the Bloomberg Terminal alongside an analysis of the power of interfaces to shape both the user and the represented information. We use the terminal as a way to critique the relationship between art acquisition and financial trading companies. We then describe some outcomes of a series of workshops themed around the idea of ‘building an alternative Bloomberg’. We conclude by offering some potential applications of a re-framed Bloomberg Terminal as an open and modular interface for engaging with issues around art and finance, both in terms of content and curation.

Since emerging around 2010, maker culture and the maker movement have drawn little attention from digital labour research. This article fills the gap by exploring sociocultural dynamics that have emerged in maker culture, such as how makers in China mobilise their agency to struggle for a path forward to achieve decent work and a better society. The article first reviews research on the Chinese maker community as well as digital labour, in particular the dualism of exploitation and workplace resistance in current digital labour research. It argues that makers, in the case studied, mobilise certain agency initiating from sociocultural dynamics beyond the framework of exploitation. The article then explicates the argument with cases collected from our fieldwork in Shenzhen’s maker community in July–August 2017. It shows makers’ practices originating from the open-source ethos, such as an awareness of sharing and mutual support in moulding a ‘micro-innovation’ model, and in creating products that aim to benefit vulnerable communities and build up a sustainable ecosystem. The article thus turns the current economic discussion on maker culture in a new direction: the sociocultural impact of the maker movement. Furthermore, it suggests that this research on the sociocultural impact fills the gap between existing digital labour research and maker studies.

The prevention of tropical forest deforestation is essential for mitigating climate change. We tested the machine learning algorithm Maxent to predict deforestation across the Peruvian Amazon. We used official annual 2001–2019 deforestation data to develop a predictive model and to test the model’s accuracy using near-real-time forest loss data for 2020. Distance from agricultural land and distance from roads were the predictor variables that contributed most to the final model, indicating that a narrower set of variables contribute nearly 80% of the information necessary for prediction at scale. The permutation importance indicating variable information not present in the other variables was also highest for distance from agricultural land and distance from roads, at 40.5% and 14.3%, respectively. The predictive model registered 73.2% of the 2020 early alerts in a high or very high risk category; less than 1% of forest cover in national protected areas were registered as very high risk, but buffer zones were far more vulnerable, with 15% of forest cover being in this category. To our knowledge, this is the first study to use 19 years of annual data for deforestation risk. The open-source machine learning method could be applied to other forest regions, at scale, to improve strategies for reducing future deforestation.

Just as tariffs lead to economic distortions and provide incentives for corruption, so do patent monopolies on prescription drugs, except the impact is often an order of magnitude larger.

Providing high-quality electron images and hyperspectral X-ray maps is a focus of many modern electron microscopy laboratories. Nevertheless, further image processing and annotations are often needed to prepare them for publications and reports. For multi-user facilities, accessibility to processing software can be a limitation either through license costs or availability of processing stations. Open-source software running on multiple platforms allows for post-acquisition data processing in-lab or on user-owned devices. We developed Probelab ReImager to supersede our vendor-supplied acquisition software's exportation by being efficient and highly customizable. This article describes its main features and capabilities.

This paper presents the results to date of the RepRap project – an ongoing project that has made and distributed freely a replicating rapid prototyper. We give the background reasoning that led to the invention of the machine, the selection of the processes that we and others have used to implement it, the designs of key parts of the machine and how these have evolved from their initial concepts and experiments, and estimates of the machine's reproductive success out in the world up to the time of writing (about 4500 machines in two and a half years).

We have developed a chemical kinetics simulation that can be used as both an educationaland research tool. The simulator is designed as an accessible, open-source project thatcan be run on a laptop with a student-friendly interface. The application can potentiallybe scaled to run in parallel for large simulations. The simulation has been successfullyused in a classroom setting for teaching basic electrochemical properties. We have shownthat this can be used for simulating fundamental molecular and chemical processes and evensimplified models of predator–prey interactions. By giving the simulated entities spatialextent in the lattice, the particles do not interpenetrate, and clusters of particles canspatially exclude one another. Our simulation demonstrates that spatial inhomogeneityleads to different results than those that are obtained by using standard ordinarydifferential equation models, as previously reported.