Smart technologies for effective reconfiguration: the FASTER approach

Current and future computing systems increasingly require that their functionality stays flexible after the system is operational, in order to cope with changing user requirements and improvements in system features, i.e. changing protocols and data-coding standards, evolving demands for support of different user applications, and newly emerging applications in communication, computing and consumer electronics. Therefore, extending the functionality and the lifetime of products requires the addition of new functionality to track and satisfy the customers needs and market and technology trends. Many contemporary products along with the software part incorporate hardware accelerators for reasons of performance and power efficiency. While adaptivity of software is straightforward, adaptation of the hardware to changing requirements constitutes a challenging problem requiring delicate solutions. The FASTER (Facilitating Analysis and Synthesis Technologies for Effective Reconfiguration) project aims at introducing a complete methodology to allow designers to easily implement a system specification on a platform which includes a general purpose processor combined with multiple accelerators running on an FPGA, taking as input a high-level description and fully exploiting, both at design time and at run time, the capabilities of partial dynamic reconfiguration. The goal is that for selected application domains, the FASTER toolchain will be able to reduce the design and verification time of complex reconfigurable systems providing additional novel verification features that are not available in existing tool flows

Resilience and food security: rethinking an ecological concept

1. Focusing on food production, in this paper we define resilience in the food security context as maintaining production of sufficient and nutritious food in the face of chronic and acute environmental perturbations. In agri-food systems, resilience is manifest over multiple spatial scales: field, farm, regional and global. Metrics comprise production and nutritional diversity as well as socio-economic stability of food supply. 2. Approaches to enhancing resilience show a progression from more ecologically-based methods at small scales to more socially-based interventions at larger scales. At the field scale, approaches include the use of mixtures of crop varieties, livestock breeds and of forage species, polycultures, and boosting ecosystem functions. Stress-tolerant crops, or with greater plasticity, provide technological solutions. 3. At the farm scale, resilience may be conferred by diversifying crops and livestock and by farmers implementing adaptive approaches in response to perturbations. Biodiverse landscapes may enhance resilience, but the evidence is weak. At regional to global scales, resilient food systems will be achieved by coordination and implementation of resilience approaches among farms, advice to farmers and targeted research. 4. Synthesis. Threats to food production are predicted to increase under climate change and land degradation. Holistic responses are needed that integrate across spatial scales. Ecological knowledge is critical, but should be implemented alongside agronomic solutions and socio-economic transformations

Assessing the impact of climate change on sweet potato in Uganda

Sweet potato is a mainstay of household food security and a major source of vitamin A across sub-Saharan Africa, and particularly in Uganda. Understanding how climate change is likely to impact on sweet potato would be useful for policymakers in Uganda making decisions to improve food security and increase resilience to climate shocks. However, sweet potato is an under-researched crop and the impacts of climate change have not been systematically analysed. The Sweet Potato Catalyst Project aims to assess the impacts of climate change on sweet potato in Uganda and develop ways for local stakeholders to access and assess this information to strengthen governance. This policy briefing note provides an overview of the research, the approach being taken and anticipated outcomes that will feed into the UNFCCC Koronovia Joint Work on Agriculture

17 ways to say yes:Toward nuanced tone of voice in AAC and speech technology

People with complex communication needs who use speech-generating devices have very little expressive control over their tone of voice. Despite its importance in human interaction, the issue of tone of voice remains all but absent from AAC research and development however. In this paper, we describe three interdisciplinary projects, past, present and future: The critical design collection Six Speaking Chairs has provoked deeper discussion and inspired a social model of tone of voice; the speculative concept Speech Hedge illustrates challenges and opportunities in designing more expressive user interfaces; the pilot project Tonetable could enable participatory research and seed a research network around tone of voice. We speculate that more radical interactions might expand frontiers of AAC and disrupt speech technology as a whole

Definition of Estrogen Receptor Pathway Critical for Estrogen Positive Feedback to Gonadotropin-Releasing Hormone Neurons and Fertility

SummaryThe mechanisms through which estrogen regulates gonadotropin-releasing hormone (GnRH) neurons to control mammalian ovulation are unknown. We found that estrogen positive feedback to generate the preovulatory gonadotropin surge was normal in estrogen receptor β knockout (ERβ) mutant mice, but absent in ERα mutant mice. An ERα-selective compound was sufficient to generate positive feedback in wild-type mice. As GnRH neurons do not express ERα, estrogen positive feedback upon GnRH neurons must be indirect in nature. To establish the cell type responsible, we generated a neuron-specific ERα mutant mouse line. These mice failed to exhibit estrogen positive feedback, demonstrating that neurons expressing ERα are critical. We then used a GnRH neuron-specific Pseudorabies virus (PRV) tracing approach to show that the ERα-expressing neurons innervating GnRH neurons are located within rostral periventricular regions of the hypothalamus. These studies demonstrate that ovulation is driven by estrogen actions upon ERα-expressing neuronal afferents to GnRH neurons

EXTRA: Towards the exploitation of eXascale technology for reconfigurable architectures

© 2016 IEEE. To handle the stringent performance requirements of future exascale-class applications, High Performance Computing (HPC) systems need ultra-efficient heterogeneous compute nodes. To reduce power and increase performance, such compute nodes will require hardware accelerators with a high degree of specialization. Ideally, dynamic reconfiguration will be an intrinsic feature, so that specific HPC application features can be optimally accelerated, even if they regularly change over time. In the EXTRA project, we create a new and flexible exploration platform for developing reconfigurable architectures, design tools and HPC applications with run-time reconfiguration built-in as a core fundamental feature instead of an add-on. EXTRA covers the entire stack from architecture up to the application, focusing on the fundamental building blocks for run-time reconfigurable exascale HPC systems: new chip architectures with very low reconfiguration overhead, new tools that truly take reconfiguration as a central design concept, and applications that are tuned to maximally benefit from the proposed run-time reconfiguration techniques. Ultimately, this open platform will improve Europe's competitive advantage and leadership in the field

The hArtes Tool Chain

This chapter describes the different design steps needed to go from legacy code to a transformed application that can be efficiently mapped on the hArtes platform

‘The Invisible Chain by Which All Are Bound to Each Other’: Civil Defence Magazines and the Development of Community During the Second World War

This article uses local collaboratively produced civil defence magazines to examine how community spirit was developed and represented within the civil defence services during the Second World War. It highlights the range of functions which the magazines performed, as well as the strategies employed by civil defence communities to manage their emotions in order to keep morale high and distract personnel from the fear and boredom experienced while on duty. The article also discusses silences in the magazines — especially around the experience of air raids — and argues that this too reflects group emotional management strategies. The significance of local social groups in developing narratives about civil defence and their workplace communities is demonstrated, and the article shows how personnel were able to engage with and refashion dominant cultural narratives of the ‘people’s war’ in order to assert their own status within the war effort

Embedding expert opinion in a Bayesian network model to predict wheat yield from spring-summer weather

Wheat yield is highly dependent on weather, Therefore, predicting its effect can improve crop management decisions. Various modelling approaches have been used to predict wheat yield including process-based modelling, statistical models, and machine learning. However, these models typically require a large data set for training or fitting. They often also have a limited ability in capturing the effects of small-scale variability, time, and duration of extreme weather events. Here, we develop a Bayesian Network (BN) model by interviewing experts including farmers, embedding their knowledge from years of experience within a quantitative model. These experts identified the period from the beginning of anthesis to the end of grain filling stage as a critical period and maximum temperature, mean temperature and precipitation as key weather variables for inclusion in the BN. To keep the time input from experts manageable, the conditional probability table for the BN was constructed based on their anticipated impact on the mean yield of different weather conditions. The model predicted the yield in the same or neighbouring class (very low, low, medium, high and very high) as the reported yield with low error rate ranging from 9.1 to 15.2% and, when used to estimate the median predicted yield, R2 ranging from 41 to 52%. Interestingly, model successfully predicted the yield in years 1998, 2007, 2012 and 2020 which had the most extreme weather events. Additionally, the more recent data, from 2012 to 2022 was predicted more accurately, especially 2022 season which was not sown yet when eliciting information and recently added to the testing data. Little difference was observed between the predictions made using model parameters based only the opinion of the farm manager from which the test data originated, and the predictions made using the average opinion of a group of 9 experts. The inclusion of causal variables in the model also provided insight into the experts’ rationale, allowing unexpected results to be explored. This methodology provides a means to rapidly develop a successful predictive model of wheat yield with limited (or no) data using expert understanding. This model could be tuned and updated with data as it becomes available

Scaling the nexus: towards integrated frameworks for analysing water, energy and food

The emergence of the water-energy-food (WEF) nexus concept following the 2011 Bonn Nexus Conference has resulted in a change to the way we perceive our natural resources. Global pressures such as climate change, and population growth have highlighted the fragility of our WEF systems, necessitating integrated solutions across multiple scales and levels. Whilst a number of frameworks and analytical tools have been developed since 2011, a comprehensive WEF nexus tool remains elusive, hindered in part by our limited data and understanding of the interdependencies and connections across the WEF systems. To achieve this, the community of academics, practitioners and policy-makers invested in WEF nexus research are addressing several critical areas that currently remain as barriers. Firstly, the plurality of scales (e.g., spatial, temporal, institutional, jurisdictional) necessitates a more comprehensive effort to assess interdependencies between water, energy and food, from household to institutional and national levels. Secondly, and closely related to scale, a lack of available data often hinders our ability to quantify physical stocks and flows of resources. In this paper, we elucidate many of the challenges that have arisen across nexus research, including the impact of multiple scales in operation across the nexus, and concomitantly, what impact these scales have on data accessibility. We review some of the critical frameworks and tools that are applied by nexus researchers and discuss some of the steps required to develop from nexus thinking to an operationalizable concept, with a consistent focus on scale and data availability