Evaporative cooling of speleothem drip water.
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ABSTRACT:
SUBMITTER: Cuthbert MO
PROVIDER: S-EPMC4044636 | biostudies-other | 2014
REPOSITORIES: biostudies-other
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Project description:We developed a 3D solar steam generator with the highest evaporation rate reported so far using a carbonized luffa sponge (CLS). The luffa sponge consisted of entangled fibers with a hierarchically porous structure; macropores between fibers, micro-sized pores in the fiber-thickness direction, and microchannels in the fiber-length direction. This structure remained after carbonization and played an important role in water transport. When the CLS was placed in the water, the microchannels in the fiber-length direction transported water to the top surface of the CLS by capillary action, and the micro-sized pores in the fiber-thickness direction delivered water to the entire fiber surface. The water evaporation rate under 1-sun illumination was 3.7 kg/m2/h, which increased to 14.5 kg/m2/h under 2 m/s wind that corresponded to the highest evaporation rate ever reported under the same condition. The high evaporation performance of the CLS was attributed to its hierarchically porous structure. In addition, it was found that the air temperature dropped by 3.6 °C when the wind passed through the CLS because of the absorption of the latent heat of vaporization. The heat absorbed by the CLS during water evaporation was calculated to be 9.7 kW/m2 under 1-sun illumination and 2 m/s wind, which was 10 times higher than the solar energy irradiated on the same area (1 kW/m2).
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Project description:ObjectiveElimination of food calories as heat could help redress the excess accumulation of metabolic energy exhibited as obesity. Prior studies have focused on the induction of thermogenesis in beige and brown adipose tissues as the application of this principle, particularly because the ?-adrenergic environment associated with thermogenic activation has been shown to have positive health implications. The counterpoint to this strategy is the regulation of heat loss; we propose that mammals with inefficient heat conservation will require more thermogenesis to maintain body temperature.MethodsSurface temperature thermography and rates of trans-epidermal water loss were integrated to profile the total heat transfer of genetically-engineered and genetically variable mice.ResultsThese data were incorporated with energy expenditure data to generate a biophysical profile to test the significance of increased rates of evaporative cooling.ConclusionsWe show that mouse skins vary considerably in their heat retention properties, whether because of naturally occurring variation (SKH-1 mice), or genetic modification of the heat-retaining lipid lamellae (SCD1, DGAT1 or Agouti Ay obese mice). In particular, we turn attention to widely different rates of evaporative cooling as the result of trans-epidermal water loss; higher rates of heat loss by evaporative cooling leads to increased demand for thermogenesis. We speculate that this physiology could be harnessed to create an energy sink to assist with strategies aimed at treating metabolic diseases.
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Project description:Rapid progress in high-speed, densely packed electronic/photonic devices has brought unprecedented benefits to our society. However, this technology trend has in reverse led to a tremendous increase in heat dissipation, which degrades device performance and lifetimes. The scientific and technological challenge henceforth lies in efficient cooling of such high-performance devices. Here, we report on evaporative electron cooling in asymmetric Aluminum Gallium Arsenide/Gallium Arsenide (AlGaAs/GaAs) double barrier heterostructures. Electron temperature, Te, in the quantum well (QW) and that in the electrodes are determined from photoluminescence measurements. At 300?K, Te in the QW is gradually decreased down to 250?K as the bias voltage is increased up to the maximum resonant tunneling condition, whereas Te in the electrode remains unchanged. This behavior is explained in term of the evaporative cooling process and is quantitatively described by the quantum transport theory.
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Project description:Cryotherapy is the most common non-pharmacological pain-relieving method. The aim of this pilot study was to ascertain whether intranasal evaporative cooling may be an effective intervention in an acute migraine attack. Studies have previously demonstrated effectiveness of a variety of cryotherapy approaches. Intranasal evaporative cooling due to vascular anatomy, allows the transfer of venous blood from nasal and paranasal mucous membranes to the dura mater, thereby providing an excellent anatomical basis for the cooling processes.We conducted a prospective, open-label, observational, pilot study. Twenty-eight patients who satisfied the International Classification of Headache Disorders (ICHD 2) diagnostic criteria for migraine were recruited. A total of 20 treatments were administered in 15 patients. All patients provided pain severity scores and migraine-associated symptoms severity scores (based on a 0-10 visual analogue scale, [VAS]).Out of the 20 treatments, intranasal evaporative cooling rendered patients' pain and symptoms free immediately after treatment, in 8 of the treatments (40%), a further 10 treatments (50%) resulted in partial pain relief (headache reduced from severe or moderate to mild) and partial symptoms relief. At 2 hours, 9 treatments (45%) provided full pain and symptoms relief, with a further 9 treatments (45%) resulting in partial pain and symptoms relief. At 24 hours, 10 treatments (50%) resulted in patients reporting pain and symptom freedom and 3 (15%) provided partial pain relief. In summary 13 patients (87%) had benefit from the treatment within 2 hours that was sustained at 24 hours.Intranasal evaporative cooling gave considerable benefit to patients with migraine, improving headache severity and migraine-associated symptoms. A further randomised, placebo controlled, double blinded, parallel clinical trial is required to further investigate the potential of this application.Clinicaltrials.gov registered trial, ClinicalTrials.gov Identifier: NCT01898455.
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Project description:The evaporative loss from global lakes (natural and artificial) is a critical component of the terrestrial water and energy balance. However, the evaporation volume of these water bodies-from the spatial distribution to the long-term trend-is as of yet unknown. Here, using satellite observations and modeling tools, we quantified the evaporation volume from 1.42 million global lakes from 1985 to 2018. We find that the long-term average lake evaporation is 1500 ± 150 km3 year-1 and it has increased at a rate of 3.12 km3 year-1. The trend attributions include an increasing evaporation rate (58%), decreasing lake ice coverage (23%), and increasing lake surface area (19%). While only accounting for 5% of the global lake storage capacity, artificial lakes (i.e., reservoirs) contribute 16% to the evaporation volume. Our results underline the importance of using evaporation volume, rather than evaporation rate, as the primary index for assessing climatic impacts on lake systems.
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Project description:MotivationClassification of individuals into disease or clinical categories from high-dimensional biological data with low prediction error is an important challenge of statistical learning in bioinformatics. Feature selection can improve classification accuracy but must be incorporated carefully into cross-validation to avoid overfitting. Recently, feature selection methods based on differential privacy, such as differentially private random forests and reusable holdout sets, have been proposed. However, for domains such as bioinformatics, where the number of features is much larger than the number of observations p?n , these differential privacy methods are susceptible to overfitting.MethodsWe introduce private Evaporative Cooling, a stochastic privacy-preserving machine learning algorithm that uses Relief-F for feature selection and random forest for privacy preserving classification that also prevents overfitting. We relate the privacy-preserving threshold mechanism to a thermodynamic Maxwell-Boltzmann distribution, where the temperature represents the privacy threshold. We use the thermal statistical physics concept of Evaporative Cooling of atomic gases to perform backward stepwise privacy-preserving feature selection.ResultsOn simulated data with main effects and statistical interactions, we compare accuracies on holdout and validation sets for three privacy-preserving methods: the reusable holdout, reusable holdout with random forest, and private Evaporative Cooling, which uses Relief-F feature selection and random forest classification. In simulations where interactions exist between attributes, private Evaporative Cooling provides higher classification accuracy without overfitting based on an independent validation set. In simulations without interactions, thresholdout with random forest and private Evaporative Cooling give comparable accuracies. We also apply these privacy methods to human brain resting-state fMRI data from a study of major depressive disorder.Availability and implementationCode available at http://insilico.utulsa.edu/software/privateEC .Contactbrett-mckinney@utulsa.edu.Supplementary informationSupplementary data are available at Bioinformatics online.
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Project description:Evidence from human genetic studies of several disorders suggests that interactions between alleles at multiple genes play an important role in influencing phenotypic expression. Analytical methods for identifying Mendelian disease genes are not appropriate when applied to common multigenic diseases, because such methods investigate association with the phenotype only one genetic locus at a time. New strategies are needed that can capture the spectrum of genetic effects, from Mendelian to multifactorial epistasis. Random Forests (RF) and Relief-F are two powerful machine-learning methods that have been studied as filters for genetic case-control data due to their ability to account for the context of alleles at multiple genes when scoring the relevance of individual genetic variants to the phenotype. However, when variants interact strongly, the independence assumption of RF in the tree node-splitting criterion leads to diminished importance scores for relevant variants. Relief-F, on the other hand, was designed to detect strong interactions but is sensitive to large backgrounds of variants that are irrelevant to classification of the phenotype, which is an acute problem in genome-wide association studies. To overcome the weaknesses of these data mining approaches, we develop Evaporative Cooling (EC) feature selection, a flexible machine learning method that can integrate multiple importance scores while removing irrelevant genetic variants. To characterize detailed interactions, we construct a genetic-association interaction network (GAIN), whose edges quantify the synergy between variants with respect to the phenotype. We use simulation analysis to show that EC is able to identify a wide range of interaction effects in genetic association data. We apply the EC filter to a smallpox vaccine cohort study of single nucleotide polymorphisms (SNPs) and infer a GAIN for a collection of SNPs associated with adverse events. Our results suggest an important role for hubs in SNP disease susceptibility networks. The software is available at (http://sites.google.com/site/McKinneyLab/software).
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Project description:'Insensible' evaporative water loss of mammals has been traditionally viewed as a passive process, but recent studies suggest that insensible water loss is under regulatory control, although the physiological role of this control is unclear. We test the hypothesis that regulation of insensible water loss has a thermoregulatory function by quantifying for the first time evaporative water loss control, along with metabolic rate and body temperature, of a heterothermic mammal during normothermia and torpor. Evaporative water loss was independent of ambient relative humidity at ambient temperatures of 20 and 30°C, but not at 25°C or during torpor at 20°C. Evaporative water loss per water vapour pressure deficit had a positive linear relationship with relative humidity at ambient temperatures of 20 and 30°C, but not at 25°C or during torpor at 20 or 25°C. These findings suggest that insensible water loss deviates from a physical model only during thermoregulation, providing support for the hypothesis that regulation of insensible evaporative water loss has a thermoregulatory role.
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Project description:During liquid evaporation, the equations for the vapor concentration in the atmosphere and for the temperature in the liquid are coupled and must be solved in an iterative manner. In the present paper, a combined field approach which unifies the coupled fields into one single hybrid field and thus makes the iteration unnecessary is proposed. By using this approach, the influences of the evaporative cooling on the evaporation of pinned sessile droplets are investigated, and its predictions are found in good agreement with the previous theoretical and experimental results. A dimensionless number Ec which can evaluate the strength of the evaporative cooling is then introduced, and the results show that both the evaporation flux along the droplet surface and the total evaporation rate of the droplet decrease as the evaporative cooling number Ec increases. For drying droplets, there exists a critical value EcCrit below which the evaporative cooling effect can be neglected and above which the significance of the effect increases dramatically. The present work may also have more general applications to coupled field problems in which all the fields have the same governing equation.
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