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The eternal adolescent? An interdisciplinary meta-narrative review of African business history
Get PDFResearch in African business history is not extensive but highly multi-disciplinary. Our review focuses on publications in key business and economic history journals to better understand the research themes favoured by these two disciplines. We follow a systematic review approach by clearly describing our search strategy and developing a definition of the field with explicit criteria for inclusion and exclusion. Through a meta-narrative approach, we demonstrate that small research niches like African business history function as interdisciplinary intersections that are sometimes too small and fragmented to form coherent research questions and agendas, and which have little consistent recognition of research contributions even within the field. We propose that meta-narrative reviewing can develop greater coherence in such interdisciplinary niches and can help to develop research agendas by providing a better overview of what historical sources are available and what gaps can be productively addressed
C-SHIFT:Efficient Cluster-based Model Fairness Control under Data Drift
No full textMachine learning models deployed in real-world scenarios must contend with data shifts that occur over time, resulting in degraded model performance and potentially exacerbating fairness concerns. Considerable research has focused separately on maintaining either model accuracy or algorithmic fairness under distribution shifts, but not both. Separately, previous results are also available for detecting the harmful regions of the training set, where data shifts have the highest impact, with the goal of reducing the cost of retraining. In this work, we propose C-SHIFT (Cluster-based Selective Harmful Shift Identification for Fairness-aware Training), a framework for efficiently managing model performance and fairness together in general data shift scenarios. Starting from an initial model with a satisfactory accuracy-fairness tradeoff, C-SHIFT activates on batches of serving data, using a novel cluster-based algorithm to identify harmful data regions that may appear in some of the clusters. C-SHIFT restores fairness and accuracy by either partially retraining or fine-tuning the original model, achieving efficiency by focusing only on the harmful data within a portion of the clusters. C-SHIFT works well with multiple fairness adjustment methods, and is not sensitive to the specific type of data shift. Because clusters are also agnostic to the data type (they only require a suitable distance metric), in principle, the approach applies to multiple data modes and is not restricted to tabular data. We evaluate the approach using three real-world datasets as well as synthetic datasets specifically designed to simulate harmful data shift scenarios. Our results indicate that C-SHIFT can restore accuracy-fairness balance with quality comparable to a baseline global retraining approach, but using a small fraction of the training/serving data, with similar results for Logistic Regression (LR) as well as nonlinear Neural Network (NN) models
Drones and war:Neglected environmental impacts and the potentiality of drone conservation
Get PDFThe use of drones in war is a well-researched topic within International Relations and Security Studies. A notable gap within the literature relates to the environmental aspects of drones in conflict contexts, which have received little attention. In contrast, there is extensive scholarship examining how the use of drones in ecological research affects various taxonomic groups of animals – and in particular different species of birds. Putting these different fields of drone research into a novel conversation with each other, and drawing on original empirical data, this interdisciplinary article examines some of the environmental risks of extensive drone use in the ongoing Russia-Ukraine war. Drones, however, are a double-edged sword; they present both risks and opportunities. An illustration of the latter is the potential of drone conservation in conflict and especially post-conflict settings. That this potential remains under-explored represents a missed opportunity to consider how drones might be creatively used to help monitor and address the environmental impacts of war. In discussing this, the article links the possibilities of drone conservation to a larger relational turn in IR
Wicked problems and the recovery of meaning:critical systems thinking for injury care in low- and middle-income countries
Get PDFInjuries cause 6 million deaths and 40 million disabilities annually. Over 90% of deaths occur in low-and-middle-income-countries (LMICs), and nearly half are preventable. This Commentary examines the possibilities and limitations of data to support injury care in LMIC settings. We frame injury care as a wicked problem with complex causality, contested goals, unintended consequences, and an incomplete evidence base. We use critical realism (CR) to address conceptual complexity and data scarcity using depth ontology and retroduction. Using exemplars (drug-related admissions, intimate-partner violence, and ambulance delays), we apply a pragmatic approach to: (1) describe patterns/distributions; (2) identify who/what may be missing or misrepresented; (3) triangulate with frontline/community intelligence to infer mechanisms and constraints, translating interpretations into feasible actions and accountabilities. CR broadens interpretation to include institutional and structural drivers (e.g. mistrust, referral fragmentation, gender norms). Routine data are indispensable but are partial. Used uncritically, they can reproduce disparities, leaving health systems to manage complex demands with limited insight. CR supports holistic analysis of how interventions interact with actors, interests, institutions, and political-economic conditions. Focusing on why disparities persist and linking routine metrics to triangulation and dialogue, CR readings can guide service adaptation and wider structural reform
Correction:Timeline for establishing a circular economy for lithium-ion batteries
Get PDFCorrection for ‘Timeline for establishing a circular economy for lithium-ion batteries’ by Jennifer M. Hartley et al., EES Batteries, 2025, 1, 1502–1514, https://doi.org/10.1039/D5EB00144G.In the original article, the information in Table 1 was misaligned due to a production error. The corrected version of Table 1 is shown below.[Table presented]The Royal Society of Chemistry apologises for these errors and any consequent inconvenience to authors and readers
Optimizing toward Discovery:AI-Driven Exploration of Lewis Acid–Base Catalysts for PET Glycolysis
Get PDFThe depolymerization of polyethylene terephthalate (PET) through efficient chemical recycling remains a central challenge in plastic waste valorization, in part because the catalyst landscape is vast and sparsely explored. Here, we present an artificial intelligence (AI)-driven discovery framework that integrates Bayesian optimization (BO), large language models (LLMs), and high-throughput robotics to accelerate the search for Lewis acid–base catalysts for PET glycolysis. Starting from a literature-guided baseline, BO used LLM-derived semantic embeddings of chemical knowledge to navigate a high-dimensional space of 11,160 candidate pairs, identifying promising candidates beyond the initial state of the art. The LLM then analyzed the experimental results to generate interpretable, data-driven hypotheses that guided further experiments and enabled inductive, human-led extrapolation beyond the predefined search space. This workflow yielded a zinc pivalate/N,N′-diethylethylenediamine catalyst delivering 95% bis(2-hydroxyethyl) terephthalate (BHET) yield in 20 min, with robust performance upon scale-up and on postconsumer PET. Mechanistic analysis supports a synergistic dual-site activation mode and informs transferable design principles. All experiments were executed on a fully autonomous AI-Chemist platform with automated reaction setup and nuclear magnetic resonance (NMR) spectroscopic analysis. Together, these results show how automation–AI–human collaboration can progress from optimization to out-of-sample discovery in large, underexplored chemical spaces
Simulations all the way up! An atheist’s response to the Fine-tuning Argument
Get PDFSo the Fine-tuning Argument goes, because it is so unlikely for the physical constants of the laws of nature to have taken the values that they in fact take, we should significantly raise our credence that God exists. Simulation Arguments argue that our world might be (or, in stronger versions, that it probably is) a mere computer simulation. This paper argues that, in light of a Simulation Argument with a particularly weak conclusion, fine-tuning reasoning instead motivates atheists to believe that we live in a computer simulation
Impurity Phases and Hydrogen Decrepitation of Sm<sub>2</sub>TM<sub>17</sub> Sintered Magnet Production Scrap
Get PDFSm2TM17 sintered magnets, (where TM = Co, Fe, Cu, Zr), are typically utilised in high temperature magnetic applications due to their magnetic properties being very stable at 200–350 °C. Sm and Co are critical materials and need to be recycled to reduce reliance on virgin material supply chains. This work explored HD processing of Sm2TM17 sintered magnet production scrap as a potential recycling technique. Sintered magnet scrap was initially analysed compositionally, microstructurally and magnetically to determine issues with magnet quality. Scrap material was then HD processed at 18 bar and 2 bar at temperatures between 25–300 °C. The resultant material was characterised in terms of hydrogen content, particle size, degassing behaviour and unit cell expansion. Production scrap magnets exhibited irregular demagnetisation traces with poor domain wall pinning behaviour. Non-magnetic ZrC inclusions likely prevented cell structure formation locally and hence were poor domain wall pinning sites. Scrap material processed at 18 bar and 2 bar required temperatures of 100 °C to allow for the greatest extent of HD reaction, reaching 0.299 Wt.% and 0.323 Wt.% hydrogen respectively. The HD behaviour of production scrap material was comparable to commercial grade magnets. Therefore, HD is a potentially viable technique for recycling Sm2TM17 sintered magnet production scrap
Law, Democracy and the Transcription of War:A Sociophenomenological Approach to Constitutional Law
No full text<i>Ab initio</i> theory of electron drag and wind forces on dislocations:bridging quantum transport and electroplasticity
No full textWe develop a conserving Keldysh field theory for a moving dislocation represented by a discrete Kanzaki force and coupled to electronic and phononic baths. Within this framework the configurational electron wind force and the electronic drag emerge as the odd and even components of a single retarded stress correlation kernel constructed from the same deformation potential vertex, placing both mechanisms on the same many body footing as standard transport coefficients. Symmetry of the slip geometry enforces a shear channel theorem in which electronic drag couples only to shear stress, while the electron wind is polar with respect to the Burgers vector, providing a microscopic mechanism for current induced texture evolution. The formalism yields closed expressions for electronic drag and electron wind in terms of Fermi surface averages of deformation potentials, band velocities and the screened Kanzaki projector, with no phenomenological relaxation times or adjustable masses. Evaluated from first principles for edge dislocations in fcc Al and basal dislocations in hcp Zn, these expressions give electronic drag coefficients that are several orders of magnitude smaller than phonon drag throughout the experimentally relevant temperature range, whereas the electron wind produces configurational stresses of order megapascals at current densities J ∼ 108–109 Am−2, consistent with reported electroplastic softening. Extension to finite magnetic field predicts a magnetoplastic analogue of magnetoresistance, in which the drag is suppressed by cyclotron deflection while the wind remains essentially field independent. The theory therefore converts wind and drag from phenomenological fit parameters into parameter free functionals of the electronic structure and provides a direct route from electronic structure calculations to dislocation mobility laws in electroplastic and magnetoplastic flow
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