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ABSTRACT Despite considerable technological advances in recent decades that have enabled the ecosystems of the deeper parts of the oceans to be discovered and explored, large knowledge gaps still exist on the biology and ecology of such ecosystems. This is largely due to challenges related to observation and experimentation in situ, and to maintaining deepwater species under ex situ experimental conditions. Deep-sea organisms have evolved life strategies and physiological adaptations (e.g. slow metabolism and growth rates, high longevity, and late maturity) that allow them to succeed in the cold and generally food-limited deep-sea environment but that may partially impair their ability to physiologically compensate for and adapt to changes in climate. Therefore, a deeper understanding of species’ biological and ecological traits, as well as their tolerance thresholds to single and cumulative climatic stressors (e.g. temperature and nutrition, pH and O2) is much needed. Most experiments to date have been conducted under short-term (i.e. acute) conditions, thereby hindering the mechanisms potentially involved in species resilience and acclimation. Studies addressing the impact of climate change on species gametogenesis, reproductive output, or larval development and physiology are also largely lacking. While efforts continue to build a knowledge base on the impacts over the physiological and ecological processes affecting individual species, it is also necessary to start to address the impacts that climate change will have on wider ecosystem functioning.

Germanium is a low-cost alternative to the highly expensive III-V semiconductors commonly used on thermophotovoltaic (TPV) devices. Despite efficiencies up to 16.5 % having been theorized in previous works, no experimental efficiencies have been reported so far for germanium-based devices. In this work, we present the first experimental germanium TPV cell efficiency measured under high view factor and high temperature irradiance conditions. Efficiencies and electric power densities up to 11.2 % and 1.43 W/cm2 have been obtained using a graphite emitter heated at 1440ºC.

Increased renewable energy penetration in isolated power systems has a clear impact on the quality of system frequency. The flywheel energy storage system (FESS) is a mature technology with a fast frequency response, high power density, high round-trip efficiency, low maintenance, no depth of discharge effects, and resilience to withstand continuous charge-discharge cycling without lifetime degradation. These FESS properties allows to effectively address the frequency quality problem. This study analyzes the contribution of a FESS to reducing frequency deviations in an isolated system that combines a diesel plant, wind farm, and pump-storage hydropower plant based on the El Hierro power system. This study approaches this analysis by comparing six different FESS governor control schemes (GCSs). Of these six GCSs, the nonlinear proportional variant (NLPV) is a singular contribution based on the NLP scheme previously developed by the same researchers. Different governor???s parameter settings for the FESS GCSs were also compared, obtained from the proposed tuning methodology that considers the renewable energy generation distribution, frequency impact, and lifetime degradation of diesel, hydraulic groups, and flywheels. The GCSs were compared in terms of average frequency deviation, Zenith and Nadir frequency difference, wear and tear of diesel electromechanical elements and Pelton turbine nozzles, flywheels cycles per hour, and FESS average state of charge. The results show that including a FESS plant considerably improves frequency regulation. The tuning criteria and GCSs have a clear influence on the results, with NLP and NLPV GCSs offering relevant improvements in frequency deviations.

The recently developed exact factorization approach condenses all electronic effects on the nuclear subsystem into scalar and vector potentials that appear in an effective time dependent Schr��dinger equation. Starting from this equation, we derive subsystem Ehrenfest identities characterizing the energy, momentum and angular momentum transfer between electrons and nuclei. An effective electromagnetic force operator induced by the electromagnetic field corresponding to the effective scalar and vector potentials appears in all three identities. The effective magnetic field has two components that can be identified with the Berry curvature calculated with (a) different cartesian coordinates of the same nucleus and (b) arbitrary cartesian coordinates of two different nuclei. (a) has a classical interpretation as the induced magnetic field felt by the nucleus, while (b) has no classical analog. Subsystem Ehrenfest identities are ideally suited for quantifying energy transfer in electron-phonon systems. With two explicit examples we demonstrate the usefulness of the new identities.

Machine-to-Machine (M2M) area networks must provide connectivity between an M2M gateway and a large number of energy-constrained M2M devices. Attaining high energy efficiency is essential in order to prolong devices lifetime. In this paper, we consider a wireless M2M area network composed of hundreds or even thousands of dormant devices that wake up periodically to transmit data upon request from a gateway. We theoretically analyze the energy efficiency of a Medium Access Control (MAC) protocol that uses a tree-splitting algorithm to resolve the collisions among devices: the Distributed Queuing (DQ) access. Computer-based simulations have been carried out to validate the accuracy of the analytical model and to evaluate and compare the energy consumption of devices using also a basic Contention Tree Algorithm (CTA) and Frame Slotted-ALOHA (FSA). Results show that DQ can reduce energy consumption in more than 35% with respect to CTA and in more than 80% with respect to FSA in dense M2M area networks with devices in compliance with the IEEE 802.15.4 physical layer. Peer Reviewed

The European Green Deal is a political milestone aiming to promote a carbon-neutral economy in the European Union. Decarbonizing the complex food sector requires the unified interaction among effective climate policies, economic instruments, and initiatives involving multiple stakeholders. Despite increasing efforts to highlight the importance of innovations and finance to achieve sustainable food supply chains (FSC), comprehensive information about related opportunities and barriers to mitigating emissions in the food sector is still under-explored. To cover this gap, this paper applies an existing industrial policy framework under the lens of the EU FSC to identify potential strategies that should help achieve the needed financial means and innovation actions, as well as to gauge political alignment across FSC stages. Methodologically, the pillars proposed in the framework are linked to multi-stakeholders’ initiatives engaged in achieving net-zero emissions. The paper highlights three main implications of the identified interlinkages. First, political directionality related to the food sector should be more comprehensively tailored to account for the specificities of all stages of the FSC. Second, research and development projects shall likewise cover all stages, instead of emphasizing only food production and agricultural systems. Finally, multiple stakeholders are crucial as promoters of technology and innovation towards a green economy. Nevertheless, initiatives should be integrated into political discussions in order to promote civil awareness, sustainable food and services demand, aligned to political guidelines.