Effects of Water Temperature on Activities of Metabolic Enzymes of Juvenile Siganus guttatus

Background: Temperature is one of the most important environmental factors affecting the survival, growth and metabolism of fish. The current study was aimed to study the effects of water temperature on the metabolic enzyme activities of juvenile Siganus guttatus. Methods: The juveniles were domesticated at 28±1°C for two weeks and then the temperature was adjusted to the target temperature groups (31°C, 27°C, 23°C and 19°C) by the gradually increasing or decreasing temperature with the change rate of 2°C per day. The experiment lasted for 70 d. At the end of the experiment, the fish were anesthetized and all the livers were dissected on ice plate and stored in the refrigerator at -80°C for the determination of enzyme activity. Result: The activities of glutamic pyruvic transaminase (GPT) and glutamic oxaloacetic transaminase (GOT), hexokinase (HK) and pyruvate kinase (PK), lipoprotein lipase (LPL) and hepatic lipase (HL) tend to be increased with the reduction of temperature. The above enzymes activities in 19°C group were highest. The activity of lactate dehydrogenase (LDH), succinate dehydrogenase (SDH) and citrate synthase (CS) was lowest in 19°C. These results suggests that 19°C had exceeded the suitable temperature range for juvenile S. guttatus. At low temperature, S. guttatus mainly use fat for energy, but less anaerobic metabolism for energy.

Robustly printable freeform thermal metamaterials

Thermal metamaterials have exhibited great potential on manipulating, controlling and processing the flow of heat, and enabled many promising thermal metadevices, including thermal concentrator, rotator, cloak, etc. However, three long-standing challenges remain formidable, i.e., transformation optics-induced anisotropic material parameters, the limited shape adaptability of experimental thermal metadevices, and a priori knowledge of background temperatures and thermal functionalities. Here, we present robustly printable freeform thermal metamaterials to address these long-standing difficulties. This recipe, taking the local thermal conductivity tensors as the input, resorts to topology optimization for the freeform designs of topological functional cells (TFCs), and then directly assembles and prints them. Three freeform thermal metadevices (concentrator, rotator, and cloak) are specifically designed and 3D-printed, and their omnidirectional concentrating, rotating, and cloaking functionalities are demonstrated both numerically and experimentally. Our study paves a powerful and flexible design paradigm toward advanced thermal metamaterials with complex shapes, omnidirectional functionality, background temperature independence, and fast-prototyping capability.

Inflation story: slow-roll and beyond

We present constraints on inflationary dynamics and features in the primordial power spectrum of scalar perturbations using the Cosmic Microwave Background temperature, polarization data from Planck 2018 data release and updated likelihoods. We constrain the slow-roll dynamics using Hilltop Quartic Potential and Starobinsky R + R 2 model in the Einstein frame using the Planck 2018 binned Plik likelihood. Using the Hilltop as base potential, we construct Whipped Inflation potential to introduce suppression in the scalar power spectrum at large angular scales. We notice marginal (68% C.L.) preference of suppression from the large scale temperature angular power spectrum. However, large-scale E-mode likelihood based on high frequency instrument cross spectrum, does not support this suppression and in the combined data the preference towards the suppression becomes negligible. Based on the Hilltop and Starobinsky model, we construct the Wiggly Whipped Inflation potentials to introduce oscillatory features along with the suppression. We use unbinned data from the recently released CamSpec v12.5 likelihood which updates Planck 2018 results. We compare the Bayesian evidences of the feature models with their baseline slow-roll potentials. We find that the complete slow-roll baseline potential is moderately preferred against potentials which generate features. Compared to Planck 2015 PlikHM bin1 likelihood, we find that the significance of sharp features has decreased owing to the updates in the data analysis pipeline. We also compute the bispectra for the best fit candidates obtained from our analysis.

Constraining Cosmic Microwave Background Temperature Evolution With Sunyaev–Zel’Dovich Galaxy Clusters from the Atacama Cosmology Telescope

The Sunyaev–Zel’dovich (SZ) effect introduces a specific distortion of the blackbody spectrum of the cosmic microwave background (CMB) radiation when it scatters off hot gas in clusters of galaxies. The frequency dependence of the distortion is only independent of the cluster redshift when the evolution of the CMB radiation is adiabatic. Using 370 clusters within the redshift range 0.07 ≲ z ≲ 1.4 from the largest SZ-selected cluster sample to date from the Atacama Cosmology Telescope, we provide new constraints on the deviation of CMB temperature evolution from the standard model α = 0.017 − 0.032 + 0.029 , where T ( z ) = T 0 1 + z 1 − α . This result is consistent with no deviation from the standard adiabatic model. Combining it with previous, independent data sets we obtain a joint constraint of α = −0.001 ± 0.012. Attributing deviation from adiabaticity to the decay of dark energy, this result constrains its effective equation of state w eff = − 0.998 − 0.010 + 0.008 .

Does apparent temperature modify the effects of air pollution on respiratory disease hospital admissions in an industrial area of South Africa?

Background: Temperature and air pollution are often treated as separate risk factors and very few studies have investigated effect modification by temperature on air pollution, and the impact of this interaction on human health in Africa. This study therefore investigated the modifying effects of temperature on the association between air pollution and Respiratory disease (RD) hospital admission in South Africa. Methods: RD admission data (ICD10 J00-J99) were obtained from two hospitals located in Secunda, South Africa beween 1 January 2011 to 31 October 2016. NO2, SO2, PM10, PM2.5, temperature and relative humidity data were obtained from the South African Weather Services. A case-crossover epidemiological study design was applied and lag0-1 was used. Models were adjusted for public holidays and Apparent Temperature (Tapp). Tapp was classified as warm (Tapp>75th percentile), cold (Tapp<25th percentile) and normal (Tapp 25th-75th percentile). Results: Of the 14 568 RD admissions, approximately equal number of females and males were admitted. The average daily NO2, SO2, PM2.5 and PM10 levels were 12.4 μm/m3, 8.5 μm/m3, 32.3 μm/m3 and 68.6 μm/m3, respectively. Overall, a 10 μm/m3 increase in SO2 on warm days was associated with an increase in RD hospital admissions among the patients by 8.5% (95% Conf. Int: 0.4%, 17.2%) and 8.4% (95% Conf. Int: 0.3%, 17.1%) after adjustment for PM2.5 and PM10 respectively. However, increasing PM2.5 or PM10 by 10 μm/m3 was associated with an increase in RD hospital admissions when the temperature was normal after adjusting for SO2. On cold days there were significant associations between the SO2 and RD admissions among the 0-14 year age group after adjusting for either PM2.5 (6.5%; 95% Conf.Int: 0.9%, 12.4%) or PM10 (5.5%; 95% Conf.Int: 0.3%, 11.1%). Conclusions: SO2 was affected by extremes of temperature while the particulate matters had effect on RD admission during normal temperature in Secunda.

Wrist and Forehead Temperature Measurement as Screening Methods During the COVID-19 Pandemic

Background: Temperature screening checkpoints have become widely distributed during the COVID-19 pandemic, using various contactless methods of temperature measurement, including wrist and forehead measurement. Aim: In this study we aim to investigate the sensitivity and specificity of these two temperature measurement methods – wrist and forehead – compared with the standards of sublingual or axillary measurement. We also aim to investigate the influence of age, gender, device brand and diurnal effect on the temperature reading. Methods: Participants were randomly assigned to one of two groups, each group using a different temperature measurement device. All participants had their forehead and wrist temperature measured, and this was compared to their axillary or sublingual readings. Results: The area under the curve for wrist measurement was 0.49 (95% CI 0.34 and 0.64), p>0.05, with a sensitivity of 46.2% and specificity of 53.3%, while the area under the curve for forehead measurement was 0.70 (95% CI 0.51, 0.89), p<0.05, with a sensitivity of 23.1% and specificity of 76.9%, PPV 1.59% and NPV 97.7%. Conclusion: Wrist and forehead temperature measurement is not accurate in detecting fever during the ongoing COVID-19 pandemic. Although forehead measurement is also not an ideal method, it nevertheless appears more consistent than wrist measurement.

Numerical investigation of induced thermal impacts from high-temperature thermal energy storage in porous aquifers

&lt;p&gt;High-temperature aquifer thermal energy storage (HT-ATES) in the geological subsurface will affect the temperature distribution in and close to the storage site, with potential impacts on groundwater flow and biogeochemistry. Quantification of the subsurface space affected by a HT-ATES operation is thus required as one basis for urban subsurface space planning, which would allow to address potential competitive and conflicting uses of the urban subsurface. Therefore, this study shows a quantitative evaluation of induced thermal impacts and subsurface space required for a synthetic ATES operated at varying temperature levels.&lt;/p&gt;&lt;p&gt;A hypothetic seasonal HT-ATES operation is simulated using the coupled groundwater flow and heat transport code OpenGeoSys. A well doublet system consisting of fully screened &amp;#8220;warm&amp;#8221; and &amp;#8220;cold&amp;#8221; wells 500 m apart is used for the storage operation. A sandy aquifer typical for the North German Basin at a depth of 110 m and with a thickness of 20 m in between two confining impermeable layers is used as storage formation. Seasonal cyclic storage is simulated for 20 years, assuming charging and discharging for six months each. During charging, water with the aquifer background temperature of 13&amp;#176;C is extracted at the &quot;cold&quot; well, heated to 70&amp;#176;C and reinjected at the &amp;#8220;warm&amp;#8221; well using a pumping rate of 30 m&amp;#179;/h. During discharging, the stored hot water is retrieved at the &quot;warm&quot; well using the same pumping rate and reinjected at the &amp;#8220;cold&amp;#8221; well after heat extraction at aquifer background temperature.&lt;/p&gt;&lt;p&gt;The simulation results show that during a single storage cycle using a storage temperature of 70&amp;#176;C 7.51 GWh of thermal energy is injected, of which 4.79 GWh can be retrieved. This corresponds to a thermal recovery factor of 63.8% and thus an effective storage capacity of 0.43&amp;#160;kWh/m&lt;sup&gt;3&lt;/sup&gt;/K can be deduced in relation to the heat capacity of the storage medium. For storage temperatures of 18&amp;#176;C, 30&amp;#176;C and 50&amp;#176;C, the effective storage capacity is 0.56 kWh/m&lt;sup&gt;3&lt;/sup&gt;/K, 0.55 kWh/m&lt;sup&gt;3&lt;/sup&gt;/K and 0.49 kWh/m&lt;sup&gt;3&lt;/sup&gt;/K, respectively. By delineating the subsurface volume with a temperature increase larger than 1&amp;#176;C, the subsurface space used for and affected by the storage operation at the storage temperature of 70 &amp;#176;C is determined to be 10.56 million m&amp;#179;. In relation to the retrieved thermal energy, a subsurface volume of 2.2 m&lt;sup&gt;3 &lt;/sup&gt;is thus required to retrieve one kWh of heat energy at 70 &amp;#176;C injection temperature. At lower temperatures of 18&amp;#176;C, 30&amp;#176;C and 50&amp;#176;C, the subsurface space required is 1.77 m&lt;sup&gt;3&lt;/sup&gt;/kWh, 1.54 m&lt;sup&gt;3&lt;/sup&gt;/kWh and 1.76 m&lt;sup&gt;3&lt;/sup&gt;/kWh, respectively. The lower effective storage capacity and the relatively larger required space, which correspond to a lower thermal recovery factor, are caused by induced thermal convection and higher heat losses by conduction at higher temperatures.&lt;/p&gt;

Drivers of Surface Downwelling Longwave Irradiance Changes from 1984 through 2017

&lt;p&gt;Relatively few studies have taken observationally driven approaches toward understanding the impact that atmospheric gases and temperatures have on surface downwelling longwave irradiance (SDLI) changes. This is despite the fact that changes in SDLI contribute significantly to climate change. Using reanalysis, observations, and the Rapid Radiative Transfer Model Global (RRTMG; Mlawer et al. 1997; Iacono et al. 2008), we linearly separate the contributions to SDLI changes from 1984 through 2017 caused by the following variables: atmospheric temperature, H&lt;sub&gt;2&lt;/sub&gt;O, CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt;, N&lt;sub&gt;2&lt;/sub&gt;O, CFC-11, and CFC-12. The results show that spatial and temporal variations in SDLI are primarily caused by spatial and temporal variations in atmospheric temperatures and water vapor amounts. Specifically, we find that atmospheric temperatures and water vapor amounts contribute about 10 times more to SDLI variations from 1984 through 2017 than the remaining greenhouse gases. Climatologically, spatial variability in atmospheric temperature and water vapor also play a role in determining the impact on SDLI of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt;, N&lt;sub&gt;2&lt;/sub&gt;O, CFC-11, and CFC-12. SDLI trends directly attributable to CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt;, N&lt;sub&gt;2&lt;/sub&gt;O, CFC-11, and CFC-12 are strongest over regions with climatologically high temperatures and low water vapor amounts. In other words, the impact of the greenhouse gases varies in space, with its strength depending on the background temperature and moisture fields, even if the change in gas mixing ratio is spatially uniform. Finally, CO&lt;sub&gt;2 &lt;/sub&gt;contributed 10 times more to the SDLI trends of 0.05-0.30 W m&lt;sup&gt;-2&lt;/sup&gt; / decade (depending on location) from 1984 through 2017 than any other greenhouse gas.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;