The effect of other neuroendocrine hormones in the regulation of adipose tissue thermogenesis.
Read More...Exploring a new mechanism controlling thermogenesis of adipose tissue
The effect of other neuroendocrine hormones in the regulation of adipose tissue thermogenesis.
Read More...Thermoelectric cooling in greenhouses: Implications for small-holder production
The authors set to test a system that would help with the dehumidification and overall management of greehouses.
Read More...Weather-based power outage prediction in New York City: An ensemble machine learning approach
This study contributes to our understanding of how urban energy systems respond to climate variability and inform strategies for enhancing power grid resilience. The findings can help inform urban planners and infrastructure developers by identifying the factors that make regions within a power grid more vulnerable.
Read More...Modelling effects of alkylamines on sea salt aerosols using the Extended Aerosols and Inorganics Model
With monitoring of climate change and the evolving properties of the atmosphere more critical than ever, the authors of this study take sea salt aerosols into consideration. These sea salt aerosols, sourced from the bubbles found at the surface of the sea, serve as cloud condensation nuclei (CCN) and are effective for the formation of clouds, light scattering in the atmosphere, and cooling of the climate. With amines being involved in the process of CCN formation, the authors explore the effects of alkylamines on the properties of sea salt aerosols and their potential relevance to climate change.
Read More...The Effect of Common Cations on DNA Degradation
Heating of DNA-containing solutions is a part of many experiment protocols, but it can also cause damage and degradation of the DNA molecules, potentially leading to error in the experimental results. The authors of this paper investigate whether the presence of certain cations during heating can stabilize the DNA polymer and aid the preservation of the molecule.
Read More...Biowaste to Biofuel: Using Methane-Producing Microorganisms Found in Soil Samples from Local Wetlands
Methane is a naturally-occurring gas that could be utilized as a renewable source of energy. In this study, authors isolated microorganisms from the Puget Sound region that could produce methane biofuel from composted waste.
Read More...The ecological mysteries of Opheodesoma spectabilis : Seasonal trends, habitat preferences, and climate responses
This study examines how environmental conditions influence the abundance and ecological role of the sea cucumber Opheodesoma spectabilis in Kāneʻohe Bay. Field observations and laboratory experiments showed that the species is more common in algae-dominated sandy habitats, where it improves water clarity and increases dissolved oxygen through bioturbation. However, exposure to very high temperatures caused rapid mortality, suggesting that marine heat waves could threaten this species and the ecological functions it provides.
Read More...Too hot to work? Heat waves, household income, and labor adaptation in India
Paper found that heat waves in India are linked to lower household income, agricultural income, and consumption, with agriculture being affected the most. It also suggests farm workers may adapt to extreme heat over time by increasing labor inputs despite rising temperatures.
Read More...Variation, relationship, and trade-offs of leaf traits in large and small deciduous broadleaf tree species
The authors access a panel of leaf traits across ten deciduous tree species to explore adaptive strategies between large and small trees.
Read More...Monitoring drought using explainable statistical machine learning models
Droughts have a wide range of effects, from ecosystems failing and crops dying, to increased illness and decreased water quality. Drought prediction is important because it can help communities, businesses, and governments plan and prepare for these detrimental effects. This study predicts drought conditions by using predictable weather patterns in machine learning models.
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