Voltage-gated sodium (NaV) channel blockade by plant cannabinoids does not confer anticonvulsant effects per se

Cannabidiol (CBD) is a non-psychoactive, well-tolerated, anticonvulsant plant cannabinoid, although its mechanism(s) of seizure suppression remains unknown. Here, we investigate the effect of CBD and the structurally similar cannabinoid, cannabigerol (CBG), on voltage-gated Na+ (NaV) channels, a common anti-epileptic drug target. CBG’s anticonvulsant potential was also assessed in vivo. CBD effects on NaV channels were investigated using patch-clamp recordings from rat CA1 hippocampal neurons in brain slices, human SH-SY5Y (neuroblastoma) cells and mouse cortical neurons in culture. CBG effects were also assessed in SH-SY5Y cells and mouse cortical neurons. CBD and CBG effects on veratridine-stimulated human recombinant NaV1.1, 1.2 or 1.5 channels were assessed using a membrane potential-sensitive fluorescent dye high-throughput assay. The effect of CBG on pentyleneterazole-induced (PTZ) seizures was assessed in rat. CBD (10M) blocked NaV currents in SH-SY5Y cells, mouse cortical neurons and recombinant cell lines, and affected spike parameters in rat CA1 neurons; CBD also significantly decreased membrane resistance. CBG blocked NaV to a similar degree to CBD in both SH-SY5Y and mouse recordings, but had no effect (50-200mg/kg) on PTZ-induced seizures in rat. CBD and CBG are NaV channel blockers at micromolar concentrations in human and murine neurons and recombinant cells. In contrast to previous reports investigating CBD, CBG had no effect upon PTZ-induced seizures in rat, indicating that NaV blockade per se does not correlate with anticonvulsant effects.

Making it all work: the engineering graduate of the future, a UK perspective

High skills are today seen as being of vital importance to economies, industries, companies and individuals. The engineering industry is no exception and the graduate engineer has a key position in this regard. In the research reported in this paper, the authors use in-depth interviews with industry experts to investigate the provision of undergraduate engineering education in the UK. The current and future skill needs of industry are examined. A typology of future engineering roles and their requisite attributes is proposed. Implications for undergraduate engineering are also discussed.

Governance, agricultural intensification and land sparing in tropical South America

In this paper we address two topical questions: How do the quality of governance and agricultural intensification impact on spatial expansion of agriculture? Which aspects of governance are more likely to ensure that agricultural intensification allows sparing land for nature? Using data from the Food and Agriculture Organization, the World Bank, the World Database on Protected Areas, and the Yale Center for Environmental Law and Policy, we estimate a panel data model for six South American countries and quantify the effects of major determinants of agricultural land expansion, including various dimensions of governance, over the period 1970–2006. The results indicate that the effect of agricultural intensification on agricultural expansion is conditional on the quality and type of governance. When considering conventional aspects of governance, agricultural intensification leads to an expansion of agricultural area when governance scores are high. When looking specifically at environmental aspects of governance, intensification leads to a spatial contraction of agriculture when governance scores are high, signaling a sustainable intensification process.

The neolithisation of Liguria (NW Italy): an environmental archaeological and palaeoenvironmental perspective

The archaeological evidence compiled for Liguria has enabled the formulation of a comprehensive model of Neolithic social, technological and economic development (∼7800–5700 cal yrs BP). The model indicates that during the Early and Middle Neolithic (∼7800–6300 cal yrs BP; ‘Impressed Ware’ and ‘Square Mouthed’ pottery cultures) human activity mainly focussed on low (coastal) and mid-altitude areas. By the Late Neolithic (∼6300–5700 cal yrs BP; ‘Chassey’ culture) farming practices were taking place over a wider range of altitudes and involved transhumant pastoralism. Complementary environmental archaeological and palaeoecological records from caves, open-air sites, lakes and mires indicate that human activities had a more significant impact on the environment than previously thought. This included clearance, especially Abies, Ulmus, Fraxinus and Tilia, and woodland utilisation and management (e.g. leaf foddering), as well as cereal cultivation and animal husbandry. The influence of Middle Holocene climatic changes, especially from ∼7800 cal yrs BP, on the direction of vegetation changes and socio-economic developments during the Neolithic remain uncertain.

Extreme rainfall variability in Australia: Patterns, drivers and predictability

Leading patterns of observed monthly extreme rainfall variability in Australia are examined using an Empirical Orthogonal Teleconnection (EOT) method. Extreme rainfall variability is more closely related to mean rainfall variability during austral summer than in winter. The leading EOT patterns of extreme rainfall explain less variance in Australia-wide extreme rainfall than is the case for mean rainfall EOTs. We illustrate that, as with mean rainfall, the El Niño-Southern Oscillation (ENSO) has the strongest association with warm-season extreme rainfall variability, while in the cool-season the primary drivers are atmospheric blocking and the subtropical ridge. The Indian Ocean Dipole and Southern Annular Mode also have significant relationships with patterns of variability during austral winter and spring. Leading patterns of summer extreme rainfall variability have predictability several months ahead from Pacific sea surface temperatures (SSTs) and as much as a year in advance from Indian Ocean SSTs. Predictability from the Pacific is greater for wetter than average summer months than for months that are drier than average, whereas for the Indian Ocean the relationship has greater linearity. Several cool-season EOTs are associated with mid-latitude synoptic-scale patterns along the south and east coasts. These patterns have common atmospheric signatures denoting moist onshore flow and strong cyclonic anomalies often to the north of a blocking anti-cyclone. Tropical cyclone activity is observed to have significant relationships with some warm season EOTs. This analysis shows that extreme rainfall variability in Australia can be related to remote drivers and local synoptic-scale patterns throughout the year.

Harnessing microbiome and probiotic research in sub-Saharan Africa: recommendations from an African workshop

To augment capacity-building for microbiome and probiotic research in Africa, a workshop was held in Nairobi, Kenya, at which researchers discussed human, animal, insect, and agricultural microbiome and probiotics/prebiotics topics. Five recommendations were made to promote future basic and translational research that benefits Africans.

The real-time optimisation of DNO owned storage devices on the LV network for peak reduction

Energy storage is a potential alternative to conventional network reinforcementof the low voltage (LV) distribution network to ensure the grid’s infrastructure remainswithin its operating constraints. This paper presents a study on the control of such storagedevices, owned by distribution network operators. A deterministic model predictive control (MPC) controller and a stochastic receding horizon controller (SRHC) are presented, wherethe objective is to achieve the greatest peak reduction in demand, for a given storagedevice specification, taking into account the high level of uncertainty in the prediction of LV demand. The algorithms presented in this paper are compared to a standard set-pointcontroller and bench marked against a control algorithm with a perfect forecast. A specificcase study, using storage on the LV network, is presented, and the results of each algorithmare compared. A comprehensive analysis is then carried out simulating a large number of LV networks of varying numbers of households. The results show that the performance of each algorithm is dependent on the number of aggregated households. However, on a typical aggregation, the novel SRHC algorithm presented in this paper is shown to outperform each of the comparable storage control techniques.

Control methodologies: Peak reduction algorithms for DNO owned storage devices on the Low Voltage network

The Distribution Network Operators (DNOs) role is becoming more difficult as electric vehicles and electric heating penetrate the network, increasing the demand. As a result it becomes harder for the distribution networks infrastructure to remain within its operating constraints. Energy storage is a potential alternative to conventional network reinforcement such as upgrading cables and transformers. The research presented here in this paper shows that due to the volatile nature of the LV network, the control approach used for energy storage has a significant impact on performance. This paper presents and compares control methodologies for energy storage where the objective is to get the greatest possible peak demand reduction across the day from a pre-specified storage device. The results presented show the benefits and detriments of specific types of control on a storage device connected to a single phase of an LV network, using aggregated demand profiles based on real smart meter data from individual homes. The research demonstrates an important relationship between how predictable an aggregation is and the best control methodology required to achieve the objective.

Mathematical solutions for electricity networks in a low carbon future

Smart meters are becoming more ubiquitous as governments aim to reduce the risks to the energy supply as the world moves toward a low carbon economy. The data they provide could create a wealth of information to better understand customer behaviour. However at the household, and even the low voltage (LV) substation level, energy demand is extremely volatile, irregular and noisy compared to the demand at the high voltage (HV) substation level. Novel analytical methods will be required in order to optimise the use of household level data. In this paper we briefly outline some mathematical techniques which will play a key role in better understanding the customer's behaviour and create solutions for supporting the network at the LV substation level.

A peak reduction scheduling algorithm for storage devices on the low voltage network

Reinforcing the Low Voltage (LV) distribution network will become essential to ensure it remains within its operating constraints as demand on the network increases. The deployment of energy storage in the distribution network provides an alternative to conventional reinforcement. This paper presents a control methodology for energy storage to reduce peak demand in a distribution network based on day-ahead demand forecasts and historical demand data. The control methodology pre-processes the forecast data prior to a planning phase to build in resilience to the inevitable errors between the forecasted and actual demand. The algorithm uses no real time adjustment so has an economical advantage over traditional storage control algorithms. Results show that peak demand on a single phase of a feeder can be reduced even when there are differences between the forecasted and the actual demand. In particular, results are presented that demonstrate when the algorithm is applied to a large number of single phase demand aggregations that it is possible to identify which of these aggregations are the most suitable candidates for the control methodology.

Diversifying into technical clothing manufacture as entrepreneurial learning: a situated learning theory perspective

Purpose – The purpose of this paper is to demonstrate analytically how entrepreneurial action as learning relating to diversifying into technical clothing – i.e. a high-value manufacturing sector – can take place. This is particularly relevant to recent discussion and debate in academic and policy-making circles concerning the survival of the clothing manufacture industry in developed industrialised countries. Design/methodology/approach – Using situated learning theory (SLT) as the major analytical lens, this case study examines an episode of entrepreneurial action relating to diversification into a high-value manufacturing sector. It is considered on instrumentality grounds, revealing wider tendencies in the management of knowledge and capabilities requisite for effective entrepreneurial action of this kind. Findings – Boundary events, brokers, boundary objects, membership structures and inclusive participation that addresses power asymmetries are found to be crucial organisational design elements, enabling the development of inter- and intracommunal capacities. These together constitute a dynamic learning capability, which underpins entrepreneurial action, such as diversification into high-value manufacturing sectors. Originality/value – Through a refinement of SLT in the context of entrepreneurial action, the paper contributes to an advancement of a substantive theory of managing technological knowledge and capabilities for effective diversification into high-value manufacturing sectors.