Bambara groundnut (Vigna subterranea (L.) Verdc) has been neglected in terms of variety selection and development which has resulted in farmers growing a mixture of landraces that are not genetically characterized and are low yielding. With the need to set up a breeding programme in Malawi, it was necessary to thoroughly understand the genetic diversity (GD) present in the available germplasm. The objectives of the study were to assess Bambara genotypes GD using agro-morphological traits and SNP markers, and to identify and select high yielding Bambara genotypes. Field trials were conducted for two seasons at Bunda College. Later, genotypes were genotyped using DartSeqLD SNP markers. All data were analysed using R Package. Significant genetic variations (P < 0.001) were observed for most traits including grain yield, which suggests that genetic variability exists in Bambara groundnuts which can be exploited in breeding programmes aimed at developing high performing varieties. Based on grain yield, the study identified 18 top performing genotypes across the evaluation seasons which will be tested under farmers’ fields’ conditions. DArTseqLD grouped the genotypes into three clusters. It was noted that majority of the genotypes from the same origin clustered together. High genetic distances were observed between genotypes from Southern African and West African regions and this has important implications in parental selection for the genetic improvement of Bambara. Our results provide valuable insights about the extent of genetic variability and how parental lines can be selected for improved genetic gain in Bambara groundnuts.

Adam Smith saw the division of labour and specialisation as the driver of ‘universal opulence’, a process limited by the scope of the market. He also believed that competition was essential to ensure growth benefited the public. Yet eventually there could be a trade-off between these two mechanisms. In today’s era of global production networks, the markets at certain links in supply chains may support just one specialised supplier; and in winner-take-all digital markets there is a single supplier even at global scale. When the scope of the market is global, there may be a trade-off between specialisation and competition.

We consider the problem of controlling the drift and diffusion rate of the endowment processes of two firms such that the joint survival probability is maximized. We assume that the endowment processes are continuous diffusions, driven by independent Brownian motions, and that the aggregate endowment is a Brownian motion with constant drift and diffusion rate. Our results reveal that the maximal joint survival probability depends only on the aggregate risk-adjusted return and on the maximal risk-adjusted return that can be implemented in each firm. Here the risk-adjusted return is understood as the drift rate divided by the squared diffusion rate.

This article reports on a study to identify the new sonic challenges and opportunities for live coders, computer musicians and sonic artists using MIRLCa, a live-coding environment powered by an artificial intelligence (AI) system. MIRLCa works as a customisable worldwide sampler, with sounds retrieved from the collective online Creative Commons (CC) database Freesound. The live-coding environment was developed in SuperCollider by the author in conversation with the live-coding community through a series of workshops and by observing its use by 16 live coders, including the author, in work-in-progress sessions, impromptu performances and concerts. This article presents a qualitative analysis of the workshops, work-in-progress sessions and performances. The findings identify (1) the advantages and disadvantages, and (2) the different compositional strategies that result from manipulating a digital sampler of online CC sounds in live coding. A prominent advantage of using sound samples in live coding is its low-entry access suitable for music improvisation. The article concludes by highlighting future directions relevant to performance, composition, musicology and education.

A key insight from Adam Smith is that economists should base their conclusions about a monetary institution or policy on a careful study of the history of that institution or policy, a study that includes the experiences of other countries. To illustrate Smith’s reliance on financial history we cover five current monetary problems that have close analogies with problems that Smith discussed: (1) inflation, (2) banking panics, (3) public debt, (4) usury laws, (5) central bank digital currencies.

Chinese cross-border investments are often assumed to be state driven and a tool of Beijing's economic statecraft. However, corresponding evidence remains inconclusive. This article examines mainland Chinese direct investments in Taiwan and finds that they are not particularly effective tools of economic statecraft. Their excessive politicization and the sheer possibility that investments could be used for Beijing's economic statecraft resulted in a considerable pushback by Taiwan's government, bureaucrats and civil society against large and sensitive investments. The agency enjoyed by Taiwan hindered Beijing from deploying cross-Strait direct investments for political purposes, and Beijing has not openly promoted or supported such investments in Taiwan. Moreover, cross-border direct investments are by nature less exploitable for political purposes because they involve company-level commercial and entrepreneurial decisions. This sets them apart from other forms of economic statecraft, such as sanctions or trade restrictions, where the state has greater influence. Mainland Chinese companies have had limited commercial interests in Taiwan, and the investments that have been made there do not appear to have triggered significant political or security externalities. These findings suggest more generally that foreign direct investment might not be particularly effective as a tool of economic statecraft.

Over the past decade, there have been increasing numbers of displaced scholars from the Middle East and Africa who have come under sustained pressures and threats from their governments; only a few of them have been able to relocate to European and North American academia through scholarships and grants.1 Even these temporary solutions for displaced scholars rarely result in sustainable institutional solidarity in the form of permanent teaching or professorial positions. The lack of institutional support, coupled with discriminatory and racialized immigration policies, pushes these few fortunate scholars to either accept exploitative conditions perpetuated by the neoliberal economy or leave academia altogether to support their families. These challenges, along with draconian economic sanctions and restrictions imposed by the US Treasury Department Office of Foreign Assets Control (OFAC) on citizens of countries such as Syria, Sudan, Iran, and Cuba are only a snapshot of what displaced scholars endure on a daily basis while trying to do research, care for their families, and compete with scholars with privileged citizenship status for shrinking opportunities in the academic job market.

Machine Learning is a powerful tool for astrophysicists, which has already had significant uptake in the community. But there remain some barriers to entry, relating to proper understanding, the difficulty of interpretability, and the lack of cohesive training. In this discussion session we addressed some of these questions, and suggest how the field may move forward.