Electricity supply and use among rural and peri-urban households and small firms in Nigeria

Improving access to energy services among the underserved requires understanding the status quo in energy access and estimating future energy requirements of energy service provision. In this paper, we present a novel survey dataset collected in 2021 within the framework of the PeopleSuN project. Across three Nigerian geopolitical zones, a total of 3,599 households and 1,122 small and medium-sized enterprises were surveyed. The sample is representative of grid-electrified regions of each zone, excluding urban centres. Our surveys collect data on demographic and socioeconomic characteristics, energy access and supply quality, electrical appliance ownership and usage time, cooking solutions, capabilities, and preferences. We encourage academic use of the data presented and suggest three avenues of further research: (1) modelling appliance ownership likelihoods, electricity consumption levels and energy service needs in un-electrified regions; (2) modelling the integration of decentralised renewable and battery storage solutions to address high usage of diesel generators in peri-urban regions; (3) exploring broader issues of multi-dimensional energy access, access to decent living standards and climate vulnerability.Comment: Revised edition: Summary statistics moved to the end. Related datasets review table added. More technical details on data collection adde

A fast and intuitive method for calculating dynamic network reconfiguration and node flexibility

Dynamic interactions between brain regions, either during rest or performance of cognitive tasks, have been studied extensively using a wide variance of methods. Although some of these methods allow elegant mathematical interpretations of the data, they can easily become computationally expensive or difficult to interpret and compare between subjects or groups. Here, we propose an intuitive and computationally efficient method to measure dynamic reconfiguration of brain regions, also termed flexibility. Our flexibility measure is defined in relation to an a-priori set of biologically plausible brain modules (or networks) and does not rely on a stochastic data-driven module estimation, which, in turn, minimizes computational burden. The change of affiliation of brain regions over time with respect to these a-priori template modules is used as an indicator of brain network flexibility. We demonstrate that our proposed method yields highly similar patterns of whole-brain network reconfiguration (i.e., flexibility) during a working memory task as compared to a previous study that uses a data-driven, but computationally more expensive method. This result illustrates that the use of a fixed modular framework allows for valid, yet more efficient estimation of whole-brain flexibility, while the method additionally supports more fine-grained (e.g. node and group of nodes scale) flexibility analyses restricted to biologically plausible brain networks

Electricity supply quality and use among rural and peri-urban households and small firms in Nigeria

Abstract We present a household and enterprise energy survey dataset collected within the framework of the PeopleSuN project in Nigeria in 2021. Across three Nigerian geopolitical zones, a total of 3,599 households and 1,122 small and medium-sized enterprises were surveyed. The sample is designed to be representative of rural and peri-urban grid-electrified regions of each zone. Our surveys collect data on demographic and socioeconomic characteristics, energy access and supply quality, electrical appliance ownership and usage time, cooking solutions, energy related capabilities, and supply preferences. We encourage academic use of the data presented and suggest three avenues of further research: (1) modelling appliance ownership likelihoods, electricity consumption levels and energy service needs in un-electrified regions; (2) identifying supply-side and demand-side solutions to address high usage of diesel generators; (3) exploring broader issues of multi-dimensional energy access, access to decent living standards and climate vulnerability

Modeling brain network flexibility in networks of coupled oscillators: a feasibility study

Abstract Modeling the functionality of the human brain is a major goal in neuroscience for which many powerful methodologies have been developed over the last decade. The impact of working memory and the associated brain regions on the brain dynamics is of particular interest due to their connection with many functions and malfunctions in the brain. In this context, the concept of brain flexibility has been developed for the characterization of brain functionality. We discuss emergence of brain flexibility that is commonly measured by the identification of changes in the cluster structure of co-active brain regions. We provide evidence that brain flexibility can be modeled by a system of coupled FitzHugh-Nagumo oscillators where the network structure is obtained from human brain Diffusion Tensor Imaging (DTI). Additionally, we propose a straightforward and computationally efficient alternative macroscopic measure, which is derived from the Pearson distance of functional brain matrices. This metric exhibits similarities to the established patterns of brain template flexibility that have been observed in prior investigations. Furthermore, we explore the significance of the brain’s network structure and the strength of connections between network nodes or brain regions associated with working memory in the observation of patterns in networks flexibility. This work enriches our understanding of the interplay between the structure and function of dynamic brain networks and proposes a modeling strategy to study brain flexibility

Optimization of the post-crisis recovery plans in scale-free networks

General Motors or a local business, which one is it better to be stimulated in postcrisis recessions, when government stimulation is meant to overcome recessions? Due to the budget constraints, it is quite relevant to ask how government can increase the chance of economic recovery. One of the key elements to answer this question is to understand metastable features of crises in economic networks and their related hysteresis. The Ising model has been suggested for studying such features. In the homogeneous networks, one needs at least a minimum budget, to force the network to switch its local equilibria, where such a minimum is independent of the network characteristics such as the average degree. In the scale free networks however, when the government aims to push the network to switch to another equilibrium, one may wonder which nodes are to be preferably stimulated in order to minimize the cost. In this paper, it is shown that stimulation of high degree nodes costs less in general. It is also found that in scale free networks, the stimulation cost depends on the networks features such as its assortativity. Although we confine our study to the Ising model in order to tackle a problem in economics, our analysis shines lights on many other problems concerning stimulations of socio-economic systems where dynamical hysteresis appears