Has the European Union entered a bioeconomy transition? Combining an output-based approach with a shift-share analysis

The bioeconomy is a collective of activities charged with the production of biologically renewable resources or ‘biomass’ (e.g. agriculture, forestry), its diverse application (e.g. food, textiles, construction, chemicals) and subsequent reuse (e.g. compositing, waste management). Since the European Union (EU) launched its bioeconomy strategy in 2012, further bioeconomy policy initiatives have proliferated at regional, national and pan-European levels. Moreover, the EU Green Deal announced in 2019 targets a transition towards a low-carbon sustainable model of growth, food and energy security, biodiversity and natural resource management, where it is envisaged that the bioeconomy will play a key role. Despite a paucity of available data, the surge in policy interest has triggered the need for evidence-based monitoring of bioeconomy sectors and the efficient tailoring of policy support. Thus, on a Member State (MS) basis for the period 2008–2017, we (1) adopt an ‘output-based’ approach to construct a panel data of performance indicators and (2) characterise the sources of growth and transitional stage of the bioeconomy. Results reveal that the bioeconomy has maintained its relative importance within the total EU27 economy. At the EU level, agriculture and the food industry have played a key role in driving a transition in the primary and industrial bioeconomy sectors due to their significant labour productivity-enhancing impact. Four Northern MS exhibit a bioeconomy transition by modernising their bioeconomy activities and operating structural changes. Other Northern and Western EU MS are still in the early stages of a transition, whilst in Eastern and Central Europe, such a transition remains elusive.

GraphAttack

Graph structures are a natural representation of important and pervasive data. While graph applications have significant parallelism, their characteristic pointer indirect loads to neighbor data hinder scalability to large datasets on multicore systems. A scalable and efficient system must tolerate latency while leveraging data parallelism across millions of vertices. Modern Out-of-Order (OoO) cores inherently tolerate a fraction of long latencies, but become clogged when running severely memory-bound applications. Combined with large power/area footprints, this limits their parallel scaling potential and, consequently, the gains that existing software frameworks can achieve. Conversely, accelerator and memory hierarchy designs provide performant hardware specializations, but cannot support diverse application demands. To address these shortcomings, we present GraphAttack, a hardware-software data supply approach that accelerates graph applications on in-order multicore architectures. GraphAttack proposes compiler passes to (1) identify idiomatic long-latency loads and (2) slice programs along these loads into data Producer/ Consumer threads to map onto pairs of parallel cores. Each pair shares a communication queue; the Producer asynchronously issues long-latency loads, whose results are buffered in the queue and used by the Consumer. This scheme drastically increases memory-level parallelism (MLP) to mitigate latency bottlenecks. In equal-area comparisons, GraphAttack outperforms OoO cores, do-all parallelism, prefetching, and prior decoupling approaches, achieving a 2.87× speedup and 8.61× gain in energy efficiency across a range of graph applications. These improvements scale; GraphAttack achieves a 3× speedup over 64 parallel cores. Lastly, it has pragmatic design principles; it enhances in-order architectures that are gaining increasing open-source support.

Chemistry and Functionality of Cold-Pressed Macadamia Nut Oil

The rising trend in the consumption of healthy, safe, and functional foods has motivated studies on cold-pressed specialty oils, including macadamia nut oil. Cold-pressed macadamia nut oil (CPMO) is given preference by consumers over solvent extracted and refined oil because of its exceptional quality attributes and safety. This review contains a detailed presentation of the chemical properties, health benefits, and applications of CPMO. The monounsaturated fatty acids (oleic acid and palmitoleic acid) rich oil also contains a significant concentration of bioactive phytochemicals including, β-sitosterol, α-tocopherol, α-tocotrienols, ρ-hydroxybenzoic acid, and caffeic acid. Moreover, the oil has good oxidative stability. The highlighted properties offer CPMO health benefits related to the prevention of cardiovascular diseases, diabetes, cancer, high blood pressure, and neurodegenerative diseases. The fatty acid composition of CPMO allows for its diverse application in the food, cosmetic, nutraceutical, and pharmaceutical industries.

Plant Factory: A New Playground of Industrial Communication and Computing

Plant Factory is a newly emerging industry aiming at transforming crop production to an unprecedented model by leveraging industrial automation and informatics. However, today’s plant factory and vertical farming industry are still in a primitive phase, and existing industrial cyber-physical systems are not optimal for a plant factory due to diverse application requirements on communication, computing and artificial intelligence. In this paper, we review use cases and requirements for future plant factories, and then dedicate an architecture that incorporates the communication and computing domains to plant factories with a preliminary proof-of-concept, which has been validated by both academic and industrial practices. We also call for a holistic co-design methodology that crosses the boundaries of communication, computing and artificial intelligence disciplines to guarantee the completeness of solution design and to speed up engineering implementation of plant factories and other industries sharing the same demands.

Ionic Liquid-Based Gels for Applications in Electrochemical Energy Storage and Conversion Devices: A Review of Recent Progress and Future Prospects

Ionic liquids (ILs) are molten salts that are entirely composed of ions and have melting temperatures below 100 °C. When immobilized in polymeric matrices by sol–gel or chemical polymerization, they generate gels known as ion gels, ionogels, ionic gels, and so on, which may be used for a variety of electrochemical applications. One of the most significant research domains for IL-based gels is the energy industry, notably for energy storage and conversion devices, due to rising demand for clean, sustainable, and greener energy. Due to characteristics such as nonvolatility, high thermal stability, and strong ionic conductivity, IL-based gels appear to meet the stringent demands/criteria of these diverse application domains. This article focuses on the synthesis pathways of IL-based gel polymer electrolytes/organic gel electrolytes and their applications in batteries (Li-ion and beyond), fuel cells, and supercapacitors. Furthermore, the limitations and future possibilities of IL-based gels in the aforementioned application domains are discussed to support the speedy evolution of these materials in the appropriate applicable sectors.

Optimised design of systems and processes using algebraic inequalities

A method for optimising the design of systems and processes has been introduced that consists of interpreting the left- and the right-hand side of a correct algebraic inequality as the outputs of two alternative design configurations delivering the same required function. In this way, on the basis of an algebraic inequality, the superiority of one of the configurations is established. The proposed method opens wide opportunities for enhancing the performance of systems and processes and is very useful for design in general. The method has been demonstrated on systems and processes from diverse application domains. The meaningful interpretation of an algebraic inequality based on a single-variable sub-additive function led to developing a light-weight design for a supporting structure based on cantilever beams. The interpretation of a new algebraic inequality based on a multivariable sub-additive function led to a method for increasing the kinetic energy absorbing capacity during inelastic impact. The interpretation of a new inequality has been used for maximising the mass of deposited substance during electrolysis.

Tailoring Recruitment and Outreach Strategies for Underrepresented Students in Public Health Pipeline Programs

Studies have shown that racial and ethnic minority health professionals are more likely than those in the majority to work in predominantly underserved, largely minority communities. Increasing the pool of underrepresented racial and ethnic professionals could help reduce health disparities. Summer programs giving minority students public health training and experiences can increase the number who enter the health professions. This article describes recruitment strategies for obtaining a diverse pool of applicants for such a program as part of a Centers for Disease Control and Prevention funded multisite undergraduate training program intended to increase the diversity of the public health workforce. The recruitment strategies used included institutional linkages, collaborative partnerships, and interpersonal contacts. No one strategy was more effective; however, Hispanic/Latinas were more likely to be recruited through institutional linkages, but less likely to be recruited through interpersonal contacts than other female groups. Understanding successful recruitment strategies to achieve a diverse application pool for public health training programs is vital to achieve health equity.

An Extended Methodology for Sizing Solar Unmanned Aerial Vehicles: Theory and Development of a Python Framework for Design Assist

There is a growing interest in using unmanned aerial vehicles (UAVs) in the most diverse application areas from agriculture to remote sensing, that determine the need to project and define mission profiles of the UAVs. In addition, solar photovoltaic energy increases the flight autonomy of this type of aircraft, forming the term Solar UAV. This study proposes an extended methodology for sizing Solar UAVs that take off from a runway. This methodology considers mission parameters such as operating location, altitude, flight speed, flight endurance, and payload to sizing the aircraft parameters, such as wingspan, area of embedded solar cells panels, runway length required for takeoff and landing, battery weight, and the total weight of the aircraft. Using the Python language, we developed a framework to apply the proposed methodology and assist in designing a Solar UAV. With this framework, it was possible to perform a sensitivity analysis of design parameters and constraints. Finally, we performed a simulation of a mission, checking the output parameters.

Survey on Mitigating the Problems of Parabolic Reflectors for Efficient Communication

In this paper, various problems associated with parabolic reflectors, its causes and the approach to mitigate these problems are discussed. The problems include; side lobe radiations, edge diffraction, aperture blockage, cross polarisation, feed spill over, feed illumination taper, pointing error, surface error and phase error. These problems have adverse effect on the overall gain, efficiency and directivity of the antenna thereby inhibiting efficient communication process. The result of the survey reveals that, phase error tends to be the most difficult of the aforementioned problems due to the challenges associated with locating the phase centre at reflector’s focus. The aperture blockage seems to have the least method of solution, because the problem can be solved by changing the centre feed to an offset feed. Detailed investigation of these problems and the relevant solutions are necessary, since parabolic reflectors are among the most common antennas with diverse application.