A European research agenda for lifelong learning

It is a generally accepted truth that without a proper educational system no country will prosper, nor will its inhabitants. With the arrival of the post-industrial society, in Europe and elsewhere, it has become increasingly clear that people should continue learning over their entire life-spans lest they or their society suffer the dire consequences. But what does this future lifelong learning society exactly look like? And how then should education prepare for it? What should people learn and how should they do so? How can we afford to pay for all this, what are the socio-economic constraints of the move towards a lifelong-learning society? And, of course, what role can and should the educational establishment of schools and universities play? This are questions that demand serious research efforts, which is what this paper argues for

Towards data exchange formats for learning experiences in manufacturing workplaces

Manufacturing industries are currently transforming, most notably through the introduction of advanced machinery and increasing degrees of au- tomation. This has caused a shift in skills required, calling for a skills gap to be filled. Learning technology needs to embrace this change and with this contri- bution, we propose a process model for learning by experience to understand and explain learning under these changed conditions. To put this process into practice, we propose two interchange formats for capturing, sharing, and re- enacting pervasive learning activities and for describing workplaces with in- volved things, persons, places, devices, apps, and their set-up

Governance of Digital Health Data on Cooperatively Organized Platforms – a Design Thinking Approach

More and more stakeholders are collecting data for improving their services: from scientific research over public administration to commercial enterprises. Existing data management services offer few rights of co-determination for their users. Data cooperatives aim to provide a democratic alternative to this. Through such a platform cooperative members are supposed to be enabled to share their data in a self-determined way. In this paper, we present a design thinking-based user research with stakeholders of data cooperatives in a health-data context. We provide an overview of motivations, expectations, and interfaces between a cooperative and individuals as cooperative members, organizations, representatives from research, and policy makers. In an iterative process, 34 interviews were conducted with different stakeholder groups, from which 7 personas were subsequently derived. For these, 4 prototypes were developed and tested with potential users. Our results show that all interviewed groups were very interested in the concept of data cooperatives. At the same time, it proves challenging to reconcile the conflicting internal and external requirements and to implement attractive value propositions for all stakeholders

RsfA (YbeB) Proteins Are Conserved Ribosomal Silencing Factors

The YbeB (DUF143) family of uncharacterized proteins is encoded by almost all bacterial and eukaryotic genomes but not archaea. While they have been shown to be associated with ribosomes, their molecular function remains unclear. Here we show that YbeB is a ribosomal silencing factor (RsfA) in the stationary growth phase and during the transition from rich to poor media. A knock-out of the rsfA gene shows two strong phenotypes: (i) the viability of the mutant cells are sharply impaired during stationary phase (as shown by viability competition assays), and (ii) during transition from rich to poor media the mutant cells adapt slowly and show a growth block of more than 10 hours (as shown by growth competition assays). RsfA silences translation by binding to the L14 protein of the large ribosomal subunit and, as a consequence, impairs subunit joining (as shown by molecular modeling, reporter gene analysis, in vitro translation assays, and sucrose gradient analysis). This particular interaction is conserved in all species tested, including Escherichia coli, Treponema pallidum, Streptococcus pneumoniae, Synechocystis PCC 6803, as well as human mitochondria and maize chloroplasts (as demonstrated by yeast two-hybrid tests, pull-downs, and mutagenesis). RsfA is unrelated to the eukaryotic ribosomal anti-association/60S-assembly factor eIF6, which also binds to L14, and is the first such factor in bacteria and organelles. RsfA helps cells to adapt to slow-growth/stationary phase conditions by down-regulating protein synthesis, one of the most energy-consuming processes in both bacterial and eukaryotic cells

Soybean Management for Seed Composition: The Perspective of U.S. Farmers

The soybean [Glycine max (L.) Merr.] compositional quality is mainly provided by the seed concentration of protein and oil. These traits are critical for sustaining global use, and although there is demand for high protein soybean, no mechanism to differentiate production is in place. At the opposite end of the supply chain, farmers are remunerated on a mass basis without having any incentive regarding seed composition. This study evaluated farmers\u27 perspectives and knowledge on soybean quality and their propensity to adopt quality improvement technologies. Farmers from the main U.S. producing regions (n = 271) were investigated with a self-administrated survey containing 21 questions during 2020 and 2021. Our results show that 84% are unaware of the current protein and oil levels from their own production. A small portion (1.4%) make management decisions (e.g., choice of genotypes or monitor quality) based on the implications on seed quality. However, practices already in place are likely to enhance the quality of seed, namely N nutrition (via rhizobia [12.9%] or fertilizer [5.9%]) and late-season crop protection (17.1%). If farmers are financially rewarded by US$0.50 per bushel, a mindset change may occur. Based on these results, we concluded that shifts in the U.S. production system targeting protein or oil markets are possible, and the constraints are mainly related to on-farm management. However, the challenges for improving the U.S. soybean competitiveness in global or niche markets also rely upon other segments of the production chain, specifically breeders, technology suppliers, and logistical structure

Climate Change and Management Impacts on Soybean N Fixation, Soil N Mineralization, N2O Emissions, and Seed Yield

Limited knowledge about how nitrogen (N) dynamics are affected by climate change, weather variability, and crop management is a major barrier to improving the productivity and environmental performance of soybean-based cropping systems. To fill this knowledge gap, we created a systems understanding of agroecosystem N dynamics and quantified the impact of controllable (management) and uncontrollable (weather, climate) factors on N fluxes and soybean yields. We performed a simulation experiment across 10 soybean production environments in the United States using the Agricultural Production Systems sIMulator (APSIM) model and future climate projections from five global circulation models. Climate change (2020–2080) increased N mineralization (24%) and N2O emissions (19%) but decreased N fixation (32%), seed N (20%), and yields (19%). Soil and crop management practices altered N fluxes at a similar magnitude as climate change but in many different directions, revealing opportunities to improve soybean systems’ performance. Among many practices explored, we identified two solutions with great potential: improved residue management (short-term) and water management (long-term). Inter-annual weather variability and management practices affected soybean yield less than N fluxes, which creates opportunities to manage N fluxes without compromising yields, especially in regions with adequate to excess soil moisture. This work provides actionable results (tradeoffs, synergies, directions) to inform decision-making for adapting crop management in a changing climate to improve soybean production systems

Assessing causes of yield gaps in agricultural areas with diversity in climate and soils

Identification of causes of gaps between yield potential and producer yields has been restricted to small geographic areas. In the present study, we developed a novel approach for identifying causes of yield gaps over large agricultural areas with diversity in climate and soils. This approach was applied to quantify and explain yield gaps in rainfed and irrigated soybean in the North-Central USA (NC USA) region, which accounts for about one third of soybean global production. Survey data on yield and management were collected from 3568 producer fields over two crop seasons and grouped into 10 technology extrapolation domains (TEDs) according to their soil, climate, and water regime. Yield potential was estimated using a combination of crop modeling and boundary functions for water productivity and compared against highest producer yields derived from the yield distribution in each TED-year. Yield gaps were calculated as the difference between yield potential and average producer yield. Explanatory factors for yield gaps were investigated by identifying management practices that were concordantly associated with high- and low-yield fields. Management × TED interactions were then evaluated to elucidate the underlying causes of yield gaps. The chosen spatial TED framework accounted for about half of the regional variation in producer yield within the NC USA region. Across the 10 TEDs, soybean average yield potential ranged from 3.3 to 5.3 Mg ha−1 for rainfed fields and from 5.3 to 5.6 Mg ha−1for irrigated fields. Highest producer yields in each TED were similar (±12%) to the estimated yield potential. Yield gap, calculated as percentage of yield potential, was larger in rainfed (range: 15–28%) than in irrigated (range: 11–16%) soybean. Upscaled to the NC USA region, yield potential was 4.8 Mg ha−1 (rainfed) and 5.7 Mg ha−1 (irrigated), with a respective yield gap of 22 and 13% of yield potential. Sowing date, tillage, and in-season foliar fungicide and/or insecticide were identified as explanatory causes for yield variation in half or more of the 10 TEDs. However, the degree to which these three factors influenced producer yield varied across TEDs. Analysis of in-season weather helped interpret management × TED interactions. For example, yield increase due to advances in sowing date was greater in TEDs with less water limitation during the pod-setting phase. The present study highlights the strength of combining producer survey data with a spatial framework to measure yield gaps, identify management factors explaining these gaps, and understand the biophysical drivers influencing yield responses to crop management

Foxp2 Regulates Gene Networks Implicated in Neurite Outgrowth in the Developing Brain

Forkhead-box protein P2 is a transcription factor that has been associated with intriguing aspects of cognitive function in humans, non-human mammals, and song-learning birds. Heterozygous mutations of the human FOXP2 gene cause a monogenic speech and language disorder. Reduced functional dosage of the mouse version (Foxp2) causes deficient cortico-striatal synaptic plasticity and impairs motor-skill learning. Moreover, the songbird orthologue appears critically important for vocal learning. Across diverse vertebrate species, this well-conserved transcription factor is highly expressed in the developing and adult central nervous system. Very little is known about the mechanisms regulated by Foxp2 during brain development. We used an integrated functional genomics strategy to robustly define Foxp2-dependent pathways, both direct and indirect targets, in the embryonic brain. Specifically, we performed genome-wide in vivo ChIP–chip screens for Foxp2-binding and thereby identified a set of 264 high-confidence neural targets under strict, empirically derived significance thresholds. The findings, coupled to expression profiling and in situ hybridization of brain tissue from wild-type and mutant mouse embryos, strongly highlighted gene networks linked to neurite development. We followed up our genomics data with functional experiments, showing that Foxp2 impacts on neurite outgrowth in primary neurons and in neuronal cell models. Our data indicate that Foxp2 modulates neuronal network formation, by directly and indirectly regulating mRNAs involved in the development and plasticity of neuronal connections