Olfaction provides chemical information to an animal about its environment. When environmental conditions change, individuals should be able to adequately maintain function. Temperature may influence olfaction in a double manner, as it modifies the concentrations of gaseous compounds and affects biological processes. Here, we address acclimatization to environmental temperature in the olfactory system of Drosophila melanogaster using heat and cold treatments. Because the consequences of temperature shifts persist for some time after the treatment's end, comparison of olfactory behaviors at the same temperature in treated and untreated flies allows us to infer the biological effects of temperature in olfaction. At intermediate odorant concentrations heat always generates a reduction of olfactory sensitivity, as they would be expected to compensate for the increase of volatiles in the air. Cold produces the opposite effect. These changes are observed in both sexes and in natural populations as well as in standard laboratory stocks. Short applications suffice to cause detectable olfactory perception changes, but even prolonged temperature treatments have only a transitory effect. Together, these results suggest that olfaction in Drosophila underlies acclimatization to environmental temperature. However, sensitivity changes are not immediate and may cause imperfect adjustment of olfactory function for short time periods.
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http://dx.doi.org/10.1016/j.jinsphys.2009.06.009 | DOI Listing |
PLoS One
January 2025
Institute of Management, Accounting and Finance, Leuphana University Lüneburg, Lüneburg, Lower Saxony, Germany.
Climate change has heightened the need to understand physical climate risks, such as the increasing frequency and severity of heat waves, for informed financial decision-making. This study investigates the financial implications of extreme heat waves on stock returns in Europe and the United States. Accordingly, the study combines meteorological and stock market data by integrating methodologies from both climate science and finance.
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January 2025
Department of Computer Science, Khalifa University, Abu Dhabi, UAE.
A methodology is proposed, which addresses the caveat that line-of-sight emission spectroscopy presents in that it cannot provide spatially resolved temperature measurements in non-homogeneous temperature fields. The aim of this research is to explore the use of data-driven models in measuring temperature distributions in a spatially resolved manner using emission spectroscopy data. Two categories of data-driven methods are analyzed: (i) Feature engineering and classical machine learning algorithms, and (ii) end-to-end convolutional neural networks (CNN).
View Article and Find Full Text PDFActa Crystallogr B Struct Sci Cryst Eng Mater
February 2025
Institute of Low Temperature and Structure Research, Polish Academy of Sciences, 2 Okólna, Wrocław, 50-422, Poland.
X-ray structural analysis of bis(guanidinium) disodium hypodiphosphate heptahydrate, (CHN)Na(PO)·7HO revealed close Na...
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January 2025
School of Mathematics and Statistics, College of Science, Rochester Institute of Technology, Rochester, New York, United States of America.
This study presents a novel non-autonomous mathematical model to explore the intricate relationship between temperature and desert locust population dynamics, considering the influence of both solitarious and gregarious phases across all life stages. The model incorporates temperature-dependent parameters for key biological processes, including egg development, hopper growth, adult maturation, and reproduction. Theoretical analysis reveals the model's capacity for complex dynamical behaviors, such as multiple stable states and backward bifurcations, suggesting the potential for sudden and unpredictable population shifts.
View Article and Find Full Text PDFPLoS One
January 2025
College of Tourism, Hubei University, Wuhan, Hubei, China.
The study analyzed the spatial distribution characteristics, evolution rules, and driving factors of 138 China's national agricultural cultural heritage sites from 2013 to 2021 at the overall and regional levels, using kernel density analysis, Centres for standard deviation ellipse analyses, spatial autocorrelation analysis, and geographical detector analysis.The results showed that: ①From an overall perspective, the spatial pattern of China's national agricultural cultural heritage changed greatly from 2013 to 2021, with a highly uneven spatial distribution, gradually showing a distribution pattern of "widely distributed, locally concentrated". The spatial distribution of China's national agricultural cultural heritage is increasingly evident, and the spatial distribution type has evolved from discrete to clustered.
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