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Performed in cooperation with the School of Mineral Engineering, University of Washington. ; Includes bibliographical references. ; Mode of access: Internet.

Yeast volatiles double starvation survival in Drosophila .

An analytical Detailed Loop Model (DLM) has been developed to analyze the performance of solar thermosiphon water heaters with heat exchangers in storage tanks. The model has been used to study the performance of thermosiphons as a function of heat exchanger characteristics, heat transfer fluids, flow resistances, tank stratification, and tank elevation relative to the collector. The results indicate that good performance can be attained with these systems compared to thermosiphons without heat exchangers.

Energy management within microgrids under the presence of large number of renewables such as photovoltaics is complicated due to uncertainties involved. Randomness in energy production and consumption make both the prediction and optimality of exchanges challenging. In this paper, we evaluate the impact of uncertainties on optimality of different robust energy exchange strategies. To address the problem, we present AIROBE, a data-driven system that uses machine-learning-based predictions of energy supply and demand as input to calculate robust energy exchange schedules using a multiband robust optimization approach to protect from deviations. AIROBE allows the decision maker to tradeoff robustness with stability of the system and energy costs. Our evaluation shows, how AIROBE can deal effectively with asymmetric deviations and how better prediction methods can reduce both the operational cost while at the same time may lead to increased operational stability of the system.

Effective waste management is of paramount importance as it contributes significantly to environmental preservation, mitigates health hazards, and aids in the preservation of precious resources. Conversely, mishandling waste not only presents severe environmental risks but can also disrupt the balance of ecosystems and pose threats to biodiversity. The emission of carbon dioxide, methane, and greenhouse gases (GHGs) can constitute a significant factor in the progression of global warming and climate change, consequently giving rise to atmospheric pollution. This pollution, in turn, has the potential to exacerbate respiratory ailments, elevate the likelihood of cardiovascular disorders, and negatively impact overall public health. Hence, efficient management of trash is extremely crucial in any society. It requires integrating technology and innovative solutions, which can help eradicate this global issue. The internet of things (IoT) is a revolutionary communication paradigm with significant contributions to remote monitoring and control. IoT-based trash management aids remote garbage level monitoring but entails drawbacks like high installation and maintenance costs, increased electronic waste production (53 million metric tons in 2013), and substantial energy consumption for always-vigilant IoT devices. Our research endeavors to formulate a comprehensive model for an efficient and cost-effective waste collection system. It emphasizes the need for global commitment by policymakers, stakeholders, and civil society, working together to achieve a common goal. In order to mitigate the depletion of manpower, fuel resources, and time, our proposed method leverages quick response (QR) codes to enable the remote monitoring of waste bin capacity across diverse city locations. We propose to minimize the deployment of IoT devices, utilizing them only when absolutely necessary and thereby allocating their use exclusively to central garbage collection facilities. Our solution places the onus of monitoring garbage levels at the community level firmly on the shoulders of civilians, demonstrating that a critical aspect of any technology is its ability to interact and collaborate with humans. Within our framework, citizens will employ our proposed mobile application to scan QR codes affixed to waste bins, select the relevant garbage level, and transmit this data to the waste collection teams’ database. Subsequently, these teams will plan for optimized garbage collection procedures, considering parameters such as garbage volume and the most efficient collection routes aimed at minimizing both time and fuel consumption.

Symbiodiniaceae species is a dinoflagellate that plays a crucial role in maintaining the symbiotic mutualism of reef-building corals in the ocean. Reef-building corals, as hosts, provide the nutrition and habitat to endosymbiotic Symbiodiniaceae species and Symbiodiniaceae species transfer the fixed carbon to the corals for growth. Environmental stress is one of the factors impacting the physiology and metabolism of the corals-dinoflagellate association. The environmental stress triggers the metabolic changes in Symbiodiniaceae species resulting in an increase in the production of survival organelles related to storage components such as lipid droplets (LD). LDs are found as unique organelles, mainly composed of triacylglycerols surrounded by phospholipids embedded with some proteins. To date, it has been reported that investigation of lipid droplets significantly present in animals and plants led to the understanding that lipid droplets play a key role in lipid storage and transport. The major challenge of investigating endosymbiotic Symbiodiniaceae species lies in overcoming the strategies in isolating lesser lipid droplets present in its intercellular cells. Here, we review the most recent highlights of LD research in endosymbiotic Symbiodiniaceae species particularly focusing on LD biogenesis, mechanism, and major lipid droplet proteins. Moreover, to comprehend potential novel ways of energy storage in the symbiotic interaction between endosymbiotic Symbiodiniaceae species and its host, we also emphasize recent emerging environmental factors such as temperature, ocean acidification, and nutrient impacting the accumulation of lipid droplets in endosymbiotic Symbiodiniaceae species.

Accelerators for heavy-ion inertial fusion energy (HIF) have an economic incentive to fit beam tubes tightly to beams, putting them at risk from electron clouds produced by emission of electrons and gas from walls. Theory and PIC simulations suggest that the electrons will be radially trapped in the /spl ges/1 kV ion-beam potential. We are beginning studies on the High-Current Experiment (HCX) with unique capabilities to characterize electron production and trapping, the effects on ion beams, and mitigation techniques. We are measuring the flux of electrons and gas evolved from a target, whose angle to the beam can be varied between 78/spl deg/ and 88/spl deg/ from normal incidence. Quadrupole magnets are operating with a variety of internal charged particle diagnostics to measure the beam halo loss, net charge, electron ionization rate, and gas density.