The Archaeology and Materiality of Mission in Southern Africa: Introduction

The period since the late 1980s has yielded a vast body of multidisciplinary literature on mission in southern Africa. Archaeology’s contribution to this scholarship, however, has been relatively muted. In introducing this special issue on the archaeology and materiality of mission, we seek to add archaeological voices to this conversation, illustrating where contributors offer novel sources, research themes, and ways of considering encounters with Christianity. Far from simply adding material to fill the gaps left in the historical record, we argue that archaeological perspectives are well-positioned to explore ruptures and continuities through time, the tensions between peoples’ imaginations and lived realities, and how Christianity may not always have been ‘believed’ but was always materialised. Our hope is to spur a more interdisciplinary dialogue that focuses on the intellectual trajectories that archaeologists of mission pursue as much as on the objects that they find

A new measure based on degree distribution that links information theory and network graph analysis

BACKGROUND: Detailed connection maps of human and nonhuman brains are being generated with new technologies, and graph metrics have been instrumental in understanding the general organizational features of these structures. Neural networks appear to have small world properties: they have clustered regions, while maintaining integrative features such as short average pathlengths. RESULTS: We captured the structural characteristics of clustered networks with short average pathlengths through our own variable, System Difference (SD), which is computationally simple and calculable for larger graph systems. SD is a Jaccardian measure generated by averaging all of the differences in the connection patterns between any two nodes of a system. We calculated SD over large random samples of matrices and found that high SD matrices have a low average pathlength and a larger number of clustered structures. SD is a measure of degree distribution with high SD matrices maximizing entropic properties. Phi (Φ), an information theory metric that assesses a system’s capacity to integrate information, correlated well with SD - with SD explaining over 90% of the variance in systems above 11 nodes (tested for 4 to 13 nodes). However, newer versions of Φ do not correlate well with the SD metric. CONCLUSIONS: The new network measure, SD, provides a link between high entropic structures and degree distributions as related to small world properties

The Importance of Recruitment and Retention in Heliophysics: It\u27s Not Just a Pipeline Problem

A major obstacle in cultivating a robust Heliophysics (and broader scientific) community is the lack of diversity throughout science, technology, engineering, and mathematics (STEM) fields. For many years, this has been understood as a “leaky pipeline” analogy, in which predominately minority students initially interested in STEM gradually fall (or are pushed) out of the field on their way to a scientific research position. However, this ignores critical structural and policy issues which drive even later career Ph.D.s out of a career in Heliophysics. We identify here several systemic problems that inhibit many from participating fully in the Heliophysics community, including soft money pressure, lack of accessibility and equity, power imbalances, lack of accountability, friction in collaboration, and difficulties in forming mentorship bonds. We present several recommendations to empower research-supporting organizations to help create a culture of inclusion, openness, and innovative science

Heliophysics Discovery Tools for the 21st Century: Data Science and Machine Learning Structures and Recommendations for 2020-2050

Three main points: 1. Data Science (DS) will be increasingly important to heliophysics; 2. Methods of heliophysics science discovery will continually evolve, requiring the use of learning technologies [e.g., machine learning (ML)] that are applied rigorously and that are capable of supporting discovery; and 3. To grow with the pace of data, technology, and workforce changes, heliophysics requires a new approach to the representation of knowledge.Comment: 4 pages; Heliophysics 2050 White Pape

Cultivating a Culture of Inclusivity in Heliophysics

A large number of heliophysicists from across career levels, institution types, and job titles came together to support a poster at Heliophysics 2050 and the position papers for the 2024 Heliophysics decadal survey titled “Cultivating a Culture of Inclusivity in Heliophysics,” “The Importance of Policies: It’s not just a pipeline problem,” and “Mentorship within Heliophysics.” While writing these position papers, the number of people who privately shared disturbing stories and experiences of bullying and harassment was shocking. The number of people who privately expressed how burned out they were was staggering. The number of people who privately spoke about how they considered leaving the field for their and their family’s health was astounding. And for as much good there is in our community, it is still a toxic environment for many. If we fail to do something now, our field will continue to suffer. While acknowledging the ongoing growth that we as individuals must work toward, we call on our colleagues to join us in working on organizational, group, and personal levels toward a truly inclusive culture, for the wellbeing of our colleagues and the success of our field. This work includes policies, processes, and commitments to promote: accountability for bad actors; financial security through removing the constant anxiety about funding; prioritization of mental health and community through removing constant deadlines and constant last-minute requests; a collaborative culture rather than a hyper-competitive one; and a community where people can thrive as whole persons and do not have to give up a healthy or well-rounded life to succeed

Evaluating the potential for the environmentally sustainable control of foot and mouth disease in Sub-Saharan Africa

Strategies to control transboundary diseases have in the past generated unintended negative consequences for both the environment and local human populations. Integrating perspectives from across disciplines, including livestock, veterinary and conservation sectors, is necessary for identifying disease control strategies that optimise environmental goods and services at the wildlife-livestock interface. Prompted by the recent development of a global strategy for the control and elimination of foot-and-mouth disease (FMD), this paper seeks insight into the consequences of, and rational options for potential FMD control measures in relation to environmental, conservation and human poverty considerations in Africa. We suggest a more environmentally nuanced process of FMD control that safe-guards the integrity of wild populations and the ecosystem dynamics on which human livelihoods depend while simultaneously improving socio-economic conditions of rural people. In particular, we outline five major issues that need to be considered: 1) improved understanding of the different FMD viral strains and how they circulate between domestic and wildlife populations; 2) an appreciation for the economic value of wildlife for many African countries whose presence might preclude the country from ever achieving an FMD-free status; 3) exploring ways in which livestock production can be improved without compromising wildlife such as implementing commodity-based trading schemes; 4) introducing a participatory approach involving local farmers and the national veterinary services in the control of FMD; and 5) finally the possibility that transfrontier conservation might offer new hope of integrating decision-making at the wildlife-livestock interface

Integrated system for traction and battery charging of electric vehicles with universal interface to the power grid

This paper proposes an integrated system for traction and battery charging of electric vehicles (EVs) with universal interface to the power grid. In the proposed system, the power electronics converters comprising the traction drive system are also used for the battery charging system, reducing the required hardware, meaning the integrated characteristic of the system. Besides, this interface is universal, since it can be performed with the three main types of power grids, namely: (1) Single-phase AC power grids; (2) Three-phase AC power grids; (3) DC power grids. In these three types of interfaces with the power grid, as well as in the traction drive operation mode, bidirectional operation is possible, framing the integration of this system into an EV in the context of smart grids. Moreover, the proposed system endows an EV with an on-board fast battery charger, whose operation allows either fast or slow battery charging. The main contributes of the proposed system are detailed in the paper, and simulation results are presented in order to attain the feasibility of the proposed system.This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT -Fundacao para a Ciencia e Tecnologia within the Project Scope: UID/CEC/00319/2013. This work has been supported by FCT within the Project Scope DAIPESEV - Development of Advanced Integrated Power Electronic Systems for Electric Vehicles: PTDC/EEI-EEE/30382/2017. Mr. Tiago Sousa is supported by the doctoral scholarship SFRH/BD/134353/2017 granted by the Portuguese FCT agency. This work is part of the FCT project 0302836 NORTE-01-0145-FEDER-030283

Toward a next generation particle precipitation model: Mesoscale prediction through machine learning (a case study and framework for progress)

We advance the modeling capability of electron particle precipitation from the magnetosphere to the ionosphere through a new database and use of machine learning tools to gain utility from those data. We have compiled, curated, analyzed, and made available a new and more capable database of particle precipitation data that includes 51 satellite years of Defense Meteorological Satellite Program (DMSP) observations temporally aligned with solar wind and geomagnetic activity data. The new total electron energy flux particle precipitation nowcast model, a neural network called PrecipNet, takes advantage of increased expressive power afforded by machine learning approaches to appropriately utilize diverse information from the solar wind and geomagnetic activity and, importantly, their time histories. With a more capable representation of the organizing parameters and the target electron energy flux observations, PrecipNet achieves a $>$50\% reduction in errors from a current state-of-the-art model (OVATION Prime), better captures the dynamic changes of the auroral flux, and provides evidence that it can capably reconstruct mesoscale phenomena. We create and apply a new framework for space weather model evaluation that culminates previous guidance from across the solar-terrestrial research community. The research approach and results are representative of the `new frontier' of space weather research at the intersection of traditional and data science-driven discovery and provides a foundation for future efforts