Hourly Temperature Variations Research Articles

Antipyretic and Anti-Inflammatory Effects of Rectal Administration of Reduning Injection in Feverish Rats Induced by Lipopolysaccharide.

This study aimed to explore the antipyretic and anti-inflammatory effects of rectal administration of Reduning injection in feverish rats induced by lipopolysaccharide (LPS), and observe the temperature changes and inflammatory indexes. The selected rats were randomly divided into 6 groups, with 10 rats in each group, named as normal empty group, model group, intravenous group (2 mL/kg), low-dose enema group (1 mL/kg), middle-dose enema group (2 mL/kg), and high-dose enema group (4 mL/kg). The hourly temperature variations in rats injected with LPS in the abdomen were recorded. Five hours later, blood samples from the abdominal aorta were collected to monitor immunoglobulin M (IgM), immunoglobulin A (IgA), interleukin (IL)-6, and tumor necrosis factor (TNF)-α. At 5 hours, the fever peak induced by LPS appeared, and obvious antipyretic effects were observed; the effect was optimal in the medium dose enema group at 4 hours (p < 0.05); the IgM value in the enema groups, the intravenous group, and normal empty group was significantly lower than that in the model group; the IgA value in each group was higher than that in the model group, but there was no statistical significance (p > 0.05); values of IL-6 and TNF-α in each group were lower than those in the model group, and the difference was statistically significant except for the high-dose enema group (p > 0.05). Low-dose and medium-dose rectal administration of Reduning injection have inhibitory effects on IL-6, TNF-α, and IgM in feverish rats induced by LPS, but there is no obvious difference compared to intravenous administration and it could achieve an anti-inflammatory effect. There is a possibility of enhancing IgA immunity with rectal administration, but there is no obvious difference compared to intravenous administration, and rectal administration has no significant effect on mucosal immunity.

Study on Thermal Reflective Cracking of Asphalt Concrete Overlays on Concrete Pavements Under Moderate Temperature Variations Using Finite Element Model

This study investigated the effects of moderate daily temperature variations on reflective cracking in asphalt concrete (AC) overlays on Portland cement concrete (PCC) pavements using three-dimensional (3D) finite element (FE) modeling. The FE model consists of an AC overlay on top of PCC slabs, followed by aggregate base and subgrade. The year-round temperature variations were divided into discrete groups using a clustering technique and each group was applied separately in the FE model. The maximum stress and strain values associated with each temperature variation group were determined using the FE model and used as the driving force corresponding to the thermally induced damage in the AC overlay. The results show that the maximum stress and strain values in the overlay depend on the hourly temperature variation as well as the seasonal temperature profile. The daily temperature variation controls the deformation of the underlying PCC slabs, whereas the seasonal temperature profile determines the viscoelastic properties of the AC overlay. The estimated maximum tensile stress and strain values suggest that the AC overlay is primarily subjected to damage from repetitive thermal loading instead of one-time fracture events for moderate temperature variations. In addition, when the AC overlay is fully bonded to the PCC slabs, the thermal strains are much greater than the traffic induced strains, indicating a high possibility of thermal reflective cracking being the dominant damage mechanism for these cases.

Estimation of the terms acting on local 1 h surface temperature variations in Paris region: the specific contribution of clouds

Abstract. Local short-term temperature variations at the surface are mainly dominated by small-scale processes coupled through the surface energy balance terms, which are well known but whose specific contribution and importance on the hourly scale still need to be further analyzed. A method to determine each of these terms based almost exclusively on observations is presented in this paper, with the main objective being to estimate their importance in hourly near-surface temperature variations at the SIRTA observatory, near Paris. Almost all terms are estimated from the multi-year dataset SIRTA-ReOBS, following a few parametrizations. The four main terms acting on temperature variations are radiative forcing (separated into clear-sky and cloudy-sky radiation), atmospheric heat exchange, ground heat exchange, and advection. Compared to direct measurements of hourly temperature variations, it is shown that the sum of the four terms gives a good estimate of the hourly temperature variations, allowing a better assessment of the contribution of each term to the variation, with an accurate diurnal and annual cycle representation, especially for the radiative terms. A random forest analysis shows that whatever the season, clouds are the main modulator of the clear-sky radiation for 1 h temperature variations during the day and mainly drive these 1 h temperature variations during the night. Then, the specific role of clouds is analyzed exclusively in cloudy conditions considering the behavior of some classical meteorological variables along with lidar profiles. Cloud radiative effect in shortwave and longwave and lidar profiles show a consistent seasonality during the daytime, with a dominance of mid- and high-level clouds detected at the SIRTA observatory, which also affects near-surface temperatures and upward sensible heat flux. During the nighttime, despite cloudy conditions and having a strong cloud longwave radiative effect, temperatures are the lowest and are therefore mostly controlled by larger-scale processes at this time.

Increased susceptibility to temperature variation for non-accidental emergency ambulance dispatches in Shenzhen, China.

Most studies focused on the temporal trend of mortality risk associated with temperature exposure. The relative role of heat, cold, and temperature variation (TV) on morbidity and its temporal trends are explored insufficiently. This study aims to investigate the temporal trends of emergency ambulance dispatch (EAD) risk and the attributable burden of heat, cold, and hourly temperature variation (HTV). We collected time-series data of daily EAD and ambient temperature in Shenzhen from 2010 to 2017. HTV was calculated as the standard deviation of the hourly temperatures between 2 consecutive days. Quasi-Poisson generalized additive models (GAM) with a time-varying distributed lag nonlinear model (DLNM) were applied to examine temporal trends of the HTV-, heat-, and cold-EAD association. The temporal variation of the attributable fraction (AF%) and attributable number (AN) for different temperature exposures was also calculated. The largest RR was observed in extreme cold [1.30 (95% CI: 1.18, 1.43)] and moderate cold [1.25 (95% CI: 1.17, 1.34)]. Significant increasing trends in HTV-related effects and burden were observed, especially for the extreme HTV effects (P for interaction < 0.05). Decreasing trends were observed in the heat-related effect and burden, though it showed no significance (P for interaction = 0.46). There was no clear change pattern of cold-related effects and burdens. Overall, the three temperature exposure caused 13.7% of EAD, of which 4.1%, 4.3%, and 5.3% were attributed to HTV, heat, and cold, respectively. All the temperature indexes in this study, especially the cold effect, are responsible for the increased risk of EAD. People have become more susceptible to HTV over the recent decade. However, there is no clear evidence to support the temporal change of the population's susceptibility to heat and cold. Thus, in addition to heat and cold, the emergency ambulance service department should pay more attention to HTV under climate change.

Daily temperature observations in Florence at the mid-eighteenth century: the Martini series (1756–1775)

In the framework of the meteorological observations in Florence after the Medici Network (1654–1670), the earliest surviving record by Pietro Gaetano Grifoni (1751–1766) was followed and partially overlapped by the temperature series by Luca Martini (1756–1775), which has been recovered from different sources and analyzed in this paper. Martini series should be divided in two periods, the turning year being 1765, when he changed house, still in Florence. A critical data analysis and the comparison with the Grifoni contemporary series in Florence clarify the thermometric liquid and scale used in the different periods. The reconstruction of the 1756–1775 daily average temperatures is carried out here following a methodology that includes the conversion from the apparent solar time to the Central Europe Time; the transformation from single/double readings to a daily average; the analysis of the hourly temperature variation during the calendar year in the 1961–1990 reference period in Florence; the test made with the snow benchmark; and the correction of the bias due to the local microclimate in the first period. The final series (1751–1775) has been composed combining Grifoni and Martini observations, covers one quarter of the eighteenth century, and constitutes the only surviving outdoor temperature record in Florence. The comparison with other periods from the mid-seventeenth to the early-twenty-first century confirms that in the mid-eighteenth century, the temperature reached the lowest levels and that a marked warming has characterized the most recent decades. Information on the pre-industrial climatology in Florence can be useful for climatic change study.

How do weather and climate change impact the COVID-19 pandemic? Evidence from the Chinese mainland

The COVID-19 pandemic continues to expand, while the relationship between weather conditions and the spread of the virus remains largely debatable. In this paper, we attempt to examine this question by employing a flexible econometric model coupled with fine-scaled hourly temperature variations and a rich set of covariates for 291 cities in the Chinese mainland. More importantly, we combine the baseline estimates with climate-change projections from 21 global climate models to understand the pandemic in different scenarios. We found a significant negative relationship between temperatures and caseload. A one-hour increase in temperatures from 25 °C to 28 °C tends to reduce daily cases by 15.1%, relative to such an increase from −2 °C to 1 °C. Our results also suggest an inverted U-shaped nonlinear relationship between relative humidity and confirmed cases. Despite the negative effects of heat, we found that rising temperatures induced by climate change are unlikely to contain a hypothesized pandemic in the future. In contrast, cases would tend to increase by 10.9% from 2040 to 2059 with a representative concentration pathway (RCP) of 4.5 and by 7.5% at an RCP of 8.5, relative to 2020, though reductions of 1.8% and 18.9% were projected for 2080–2099 for the same RCPs, respectively. These findings raise concerns that the pandemic could worsen under the climate-change framework.

Experimental Investigation of Thermal Response of Encased Composite Beams

Many types of structures, or part of which, are directly under the exposure of the time-dependent variations of the temperature of air and solar radiation. Such thermal loads can vary the temperature of the different parts of the structural members causing undesired structural effects. In this research, an experimental study was conducted to investigate the influence of such thermal loads on composite beams. For this purpose, a concrete-encased-steel beam was instrumented with fifteen thermocouples and other sensors. The records were captured for a sunny winter day with moderately high daily air temperature difference of more than 18 oC and a solar radiation of more than 700 W/m2. The results showed that the hourly temperature variation and the sun movement in addition to the altitude angle of sun rays control the vertical and lateral temperature distributions of the beam. The maximum recorded difference between hourly maximum and minimum temperatures of the beam was 12.5 oC.

Population Adaptation Phenomena Modelled through Functional Regression

The majority of weather-related health studies use past data in regression models to model the relationship between a weather exposure and a health issue. A large variety of models have been used over the years for this purpose, progressively increasing their complexity and relevance. However, gaps still exist in the understanding of weather/health relationships which, when filled, would help predicting more accurately the impact of climate change on human health. In this purpose, the present paper introduces functional regression models for environmental epidemiology studies. These models consider continuous curves instead of series of scalar values as input and/or output. Functional models are thus flexible and able to take advantage of the whole information contained in the data to estimate the weather/health relationship. Two types of functional regression models are applied in the present work to model temperature-related cardiovascular mortality in the city of Montr&amp;#233;al, Canada. The first type of model seeks to estimate the impact of hourly temperature variations on cardiovascular mortality. The second one seeks to model how the studied relationship evolves during the year. Both applications allows new insights on the temperature/cardiovascular mortality relationship in Montr&amp;#233;al. They especially suggest physiological adaptation effects in the response of the population to temperature, either during summer or winter. From this simple application, it is hoped that functional regression models will be used in more complex studies.

High Frequency Data Acquisition System for Modelling the Impact of Visitors on the Thermo-Hygrometric Conditions of Archaeological Sites: A Casa di Diana (Ostia Antica, Italy) Case Study.

The characterization of the microclimatic conditions is fundamental for the preventive conservation of archaeological sites. In this context, the identification of the factors that influence the thermo-hygrometric equilibrium is key to determine the causes of cultural heritage deterioration. In this work, a characterization of the thermo-hygrometric conditions of Casa di Diana (Ostia Antica, Italy) is carried out analyzing the data of temperature and relative humidity recorded by a system of sensors with high monitoring frequency. Sensors are installed in parallel, calibrated and synchronized with a microcontroller. A data set of 793,620 data, arranged in a matrix with 66,135 rows and 12 columns, was used. Furthermore, the influence of human impact (visitors) is evaluated through a multiple linear regression model and a logistic regression model. The visitors do not affect the environmental humidity as it is very high and constant all the year. The results show a significant influence of the visitors in the upset of the thermal balance. When a tourist guide takes place, the probability that the hourly temperature variation reaches values higher than its monthly average is 10.64 times higher than it remains equal or less to its monthly average. The analysis of the regression residuals shows the influence of outdoor climatic variables in the thermal balance, such as solar radiation or ventilation.

Generic calibration of a simple model of diurnal temperature variations for spatial analysis of accumulated degree-days

Accumulated growing degree-days (aGDD) are widely used to predict phenological stages of plants and insects. It has been shown in the past that the best predictive performance is obtained when aGDD are computed from hourly temperature data. As the latter are not always available, models of diurnal temperature changes are often employed to retrieve the required information from data of daily minimum and maximum temperatures. In this study, we examine the performance of a well-known model of hourly temperature variations in the context of a spatial assessment of aGDD. Specifically, we examine whether a generic calibration of such a temperature model is sufficient to infer in a reliable way spatial patterns of key phenological stages across the complex territory of Switzerland. Temperature data of a relatively small number of meteorological stations is used to obtain a generic model parameterization, which is first compared with site-specific calibrations. We show that, at the local scale, the predictive skill of the generic model does not significantly differ from that of the site-specific models. We then show that for aGDD up to 800 °C d (on a base temperature of 10 °C), phenological dates predicted with aGDD obtained from estimated hourly temperature data are within ± 3 days of dates estimated on the basis of observed hourly temperatures. This suggests the generic calibration of hourly temperature models is indeed a valid approach for pre-processing temperature data in regional studies of insect and plant phenology.

Thermal and Physical Investigations into Lake Deepening Processes on Spillway Lake, Ngozumpa Glacier, Nepal

This paper investigates physical processes in the four sub-basins of Ngozumpa glacier’s terminal Spillway Lake for the period 2012–2014 in order to characterize lake deepening and mass transfer processes. Quantifying the growth and deepening of this terminal lake is important given its close vicinity to Sherpa villages down-valley. To this end, the following are examined: annual, daily and hourly temperature variations in the water column, vertical turbidity variations and water level changes and map lake floor sediment properties and lake floor structure using open water side-scan sonar transects. Roughness and hardness maps from sonar returns reveal lake floor substrates ranging from mud, to rocky debris and, in places, bare ice. Heat conduction equations using annual lake bottom temperatures and sediment properties are used to calculate bottom ice melt rates (lake floor deepening) for 0.01 to 1-m debris thicknesses. In areas of rapid deepening, where low mean bottom temperatures prevail, thin debris cover or bare ice is present. This finding is consistent with previously reported localized regions of lake deepening and is useful in predicting future deepening.

Accounting for Temperature Susceptibility of Asphalt Stiffness When Designing Bonded Concrete Overlays of Asphalt Pavements

AbstractA bonded concrete overlay of asphalt (BCOA), also known as whitetopping, is a thin concrete overlay placed upon a distressed asphalt pavement. The asphalt-resilient modulus is kept constant in current BCOA design procedures. This practice results in an underestimation of the damage as compared to when the hourly temperature variation of the asphalt is considered. The framework to establish an equivalent asphalt modulus involves generating a database of hourly middepth asphalt temperatures. This database should include hourly temperatures for different BCOA structures and a large range of geographical locations representing different climatic conditions. The hourly middepth asphalt temperatures are then used to generate hourly asphalt moduli using master curves. Through fatigue equivalency, the equivalent asphalt moduli are calculated for each month. In order to establish the relationship between the asphalt modulus and middepth temperature, the United States was divided into seven different zones ...

Investigation on Hourly and Monthly Thermal Comfort in the Humid Tropics of Malaysia

Investigations on hourly and monthly indoor neutral temperature variations in the humid tropics are limited in literature. In Malaysia, the variation of hourly outdoor mean temperature is slightly higher than the monthly mean temperature. Consequently, this leads to the hypothesis that the variation of hourly neutral temperatures might be higher than the monthly neutral temperatures. Understanding the impact of hourly and monthly temperature variation on thermal comfort will certainly provide the design direction of future indoor environments. In this study, extensive measurements from residential buildings were used to investigate the observed variation. Linear regression and Griffiths methods were explored for analyzing the results. There was almost no variation on hourly and monthly neutral temperatures within the range under study. Further research is highly recommended due to the limited data collection and the limitations of the employed methods. It is highly advised to further investigate the hourly temperature variation on thermal comfort during nighttime and early morning. This is for an accurate interpretation of the results.

A stochastic load model for an electricity market

This paper presents a stochastic load model that uses a regression equation coupled with a time series model. The model is simple but without compromising accuracy. A 24-h set of regression equations incorporates the hourly temperature variations. Weekly seasonality is handled by providing weekday and weekend non-linear regression equations. The Levenberg–Marquard method is used because of its superiority over the widely used Gauss–Newton and steepest descent methods in estimating model parameters and to avoid “slow down” in the search process, respectively. A residual discrete time series is determined by using the autoregressive integrated moving average (ARIMA) model. Test results using PJM-market load data indicate the effectiveness of the proposed model to predict the daily electricity load.

Estimating seasonal values of thermal diffusivity in thawed and frozen soils using temperature time series

Various methods have been developed to estimate the thermal diffusivity in soils from temperature time series, but all have limitations. The method described here is designed to obtain a bulk estimate of thermal diffusivity representative of the soil column during a season, or period of around three months. Hourly precision temperature measurements were recorded between August 1993 and August 1994 at eight probes in the active layer and near-surface permafrost at two sites in northern Alaska. Hourly temperature changes were calculated during the period when the soil was thawed, and used to compute the average temperature change rate (°C h −1) at each probe level. The diffusivity was estimated by relating the rates at each level using the ratio amplitude method. Bulk values for the thawed soils above permafrost were 1.5 and 2.1 × 10 −7 m 2 S −1 at Happy Valley and Barrow, respectively. Several strategies were employed to verify the methodology. The results indicate that this method is most effective in the upper part of the soil column in summer where hourly temperature variations are fairly large. Thermal diffusivity has strong time and depth dependence. By reducing this inherent variability to a single value representing the thawed soil column over the entire season, information is lost. However, it does provide an estimate as input for modeling active layer thaw at high latitudes given similar soils, vegetation cover and topography.

Analysis of a built-in storage type of solar water heater

The performance of a built-in storage type solar water heater has been analysed by using energy balances. Simple but precise expressions of the variation of water temperature with time in a tank have been derived for both day and night. The calculated hourly temperature variations of water are in close agreement with experimental data.

Analytical Prediction of the Hourly Temperature Variation in rivers

Analytical Prediction of the Hourly Temperature Variation in rivers

A suggestion for a mathematical approach to the problem of the effect of climatic factors on health

It is suggested that the effect of sudden temperature changes upon the organism may be due to the variation of two factors, whose rates of changes are functions of the temperature. It is assumed that the variations of the two factors follow differential equations which are formally identical with those of the two-factor theory of excitation, and in which the temperature formally plays the role of the stimulus. By proper choice of the parameters the two factors are made equal for any constant temperature. Assuming that the greater the absolute value of the difference of the two factors, the greater is the instability of the organism, and the greater is its susceptibility to disease, relations between the suddenness of temperature changes and disease incidence are derived. The incidence of weather-affected disease for a given period of time is found to be a linear function of the mean hourly temperature variation during that period, a relation which can be in principle verified.