Spatiotemporal Temperature Distribution Research Articles

A virtual rat for simulating environmental and exertional heat stress.

Severe cases of environmental or exertional heat stress can lead to varying degrees of organ dysfunction. To understand heat-injury progression and develop efficient management and mitigation strategies, it is critical to determine the thermal response in susceptible organs under different heat-stress conditions. To this end, we used our previously published virtual rat, which is capable of computing the spatiotemporal temperature distribution in the animal, and extended it to simulate various heat-stress scenarios, including 1) different environmental conditions, 2) exertional heat stress, 3) circadian rhythm effect on the thermal response, and 4) whole body cooling. Our predictions were consistent with published in vivo temperature measurements for all cases, validating our simulations. We observed a differential thermal response in the organs, with the liver experiencing the highest temperatures for all environmental and exertional heat-stress cases. For every 3°C rise in the external temperature from 40 to 46°C, core and organ temperatures increased by ∼0.8°C. Core temperatures increased by 2.6 and 4.1°C for increases in exercise intensity from rest to 75 and 100% of maximal O2 consumption, respectively. We also found differences as large as 0.8°C in organ temperatures for the same heat stress induced at different times during the day. Even after whole body cooling at a relatively low external temperature (1°C for 20 min), average organ temperatures were still elevated by 2.3 to 2.5°C compared with normothermia. These results can be used to optimize experimental protocol designs, reduce the amount of animal experimentation, and design and test improved heat-stress prevention and management strategies.

Seasonal evolution of ecohydrological controls on land surface temperature over complex terrain

The spatiotemporal distribution of Land Surface Temperature (LST) is linked to the partitioning of the coupled surface water and energy budgets. In watersheds with a strong seasonality in precipitation and vegetation cover, the temporal evolution of LST patterns are a signature of the interactions between the land surface and atmosphere. Nevertheless, few studies have sought to understand the topographical and ecohydrological controls on LST in regions of complex terrain. Numerical watershed models, tested against spatially distributed field and remote sensing data, can aid in linking the seasonal evolution of LST to meteorology, terrain, soil, and vegetation. In this study, we use a distributed hydrologic model to explore LST patterns in a semiarid mountain basin during the transition from a dry spring to the wetter North American monsoon (NAM). By accounting for vegetation greening through remotely sensed parameters, the model reproduces LST and surface soil moisture observations derived from ground, aircraft, and satellite platforms with good accuracy at individual sites and as spatial basin patterns. Distributed simulations reveal how LST varies with elevation, slope, and aspect and the role played by the seasonal vegetation canopy in cooling the land surface and increasing the spatial variability in LST. As a result, LST is shown to track well with ecosystem-specific changes in vegetation cover, evapotranspiration, and soil moisture during the NAM. Furthermore, vegetation greening is shown to modulate the spatial heterogeneity of LST during the NAM that should be considered in subsequent atmospheric studies in regions of complex terrain.

지난 40년간 한반도 기온의 시·공간적 분포 변화에 관한 연구

지난 40년간 한반도 기온의 시·공간적 분포 변화에 관한 연구

Generation of regional climate ensembles using Atmospheric Forcing Shifting

Ensembles of high-resolution regional climate model (RCM) simulations are crucial for assessing regional climate change and the associated uncertainties. This article presents an RCM ensemble generation technique which explores uncertainties arising from the positioning of synoptic systems in the large-scale atmospheric forcing by shifting the atmospheric fields from global climate model (GCM) runs horizontally. Here, we discuss how the so-called Atmospheric Forcing Shifting (AFS) affects temperature and precipitation over Europe for the period 1980–1984. We use ERA-40 reanalysis data in which the atmospheric fields are shifted to each direction by 25 and 50 km, respectively, to run RCM simulations with COSMO-CLM at 50-km resolution. The analysis of the AFS ensemble includes comparisons with E-OBS observations and COSMO-CLM runs driven by different GCMs. AFS has an evident effect on the spatiotemporal distributions of temperature and particularly precipitation, which is most pronounced during hydrological summer (May to October) when spatial weather patterns are more variable. Furthermore, AFS produces realistic changes in the likelihood and intensity of extreme precipitation. The changes induced by AFS depend strongly on orography, i.e. precipitation increases are likely to occur where moist air masses are shifted towards the windward mountain side and vice versa. Thus, increasing the RCM ensemble spread by means of AFS is a simple and useful method for sampling observed climate statistics and assessing the variability and changes in mean and extreme climate.

A 3-D mathematical model to identify organ-specific risks in rats during thermal stress

Early prediction of the adverse outcomes associated with heat stress is critical for effective management and mitigation of injury, which may sometimes lead to extreme undesirable clinical conditions, such as multiorgan dysfunction syndrome and death. Here, we developed a computational model to predict the spatiotemporal temperature distribution in a rat exposed to heat stress in an attempt to understand the correlation between heat load and differential organ dysfunction. The model includes a three-dimensional representation of the rat anatomy obtained from medical imaging and incorporates the key mechanisms of heat transfer during thermoregulation. We formulated a novel approach to estimate blood temperature by accounting for blood mixing from the different organs and to estimate the effects of the circadian rhythm in body temperature by considering day-night variations in metabolic heat generation and blood perfusion. We validated the model using in vivo core temperature measurements in control and heat-stressed rats and other published experimental data. The model predictions were within 1 SD of the measured data. The liver demonstrated the greatest susceptibility to heat stress, with the maximum temperature reaching 2°C higher than the measured core temperature and 95% of its volume exceeding the targeted experimental core temperature. Other organs also attained temperatures greater than the core temperature, illustrating the need to monitor multiple organs during heat stress. The model facilitates the identification of organ-specific risks during heat stress and has the potential to aid in the development of improved clinical strategies for thermal-injury prevention and management.

Latent heat flux and air temperature anomalies along an active fault zone associated with recent Iran earthquakes

Pre-earthquake physical and chemical interactions in the earth’s ground may cause anomalies in latent heat flux, air and surface temperature. Earthquakes occur when the energy accumulated in rocks releases. Sometimes, the movements of the ground cause ruptures in the earth’s surface and sometimes the two sides of an existing fault shift towards each other. In a structurally complex and inhomogeneous collision region such as the Iranian Plateau, seismicity is not the result of activity of a single fault but is due to energy discharge in fault zones hundreds of kilometers wide.Changes in latent heat flux and temperature, on and above the earth’s surface can be detected with thermal infrared (TIR) sensors such as NOAA-AVHRR, Terra/Aqua-MODIS, etc. Spatio-temporal distributions of surface latent heat flux (SLHF) and air temperature before and after two recent earthquakes in Iran have been studied. Anomalous patterns of higher SLHF formed a few days before the earthquakes of 20 Dec 2010 (6M) and 27 Jan 2011(6.5M) occurred in Kerman province and disappeared after the main events. Data analyses revealed at least 2–4°C rises in air temperature along the nearby fault zone, as well. These changes were also in accordance with the abnormal relative humidity over the region. Significant rises in SLHF and air temperature may lead us to understand the energy exchange mechanism during the earthquakes. These anomalies prior to impending earthquakes can be attributed to the thermodynamic, degassing and ionization processes which are believed to be activated by the accumulated stress in the ground, insensible movements of the tectonic blocks, and micro-fracturing in the rocks especially along area’s active faults. Continuous monitoring of these potential precursors helps in differentiating earthquake related variations from seasonal changes and atmospheric effects.

Evaluation and application of Bayesian multi-model estimation in temperature simulations

Use of multi-model ensembles from global climate models to simulate the current and future climate change has flourished as a research topic during recent decades. This paper assesses the performance of multi-model ensembles in simulating global land temperature from 1960 to 1999, using Nash-Sutcliffe model efficiency and Taylor diagrams. The future trends of temperature for different scales and emission scenarios are projected based on the posterior model probabilities estimated by Bayesian methods. The results show that ensemble prediction can improve the accuracy of simulations of the spatiotemporal distribution of global temperature. The performance of Bayesian model averaging (BMA) at simulating the annual temperature dynamic is significantly better than single climate models and their simple model averaging (SMA). However, BMA simulation can demonstrate the temperature trend on the decadal scale, but its annual assessment of accuracy is relatively weak. The ensemble prediction presents dissimilarly accurate descriptions in different regions, and the best performance appears in Australia. The results also indicate that future temperatures in northern Asia rise with the greatest speed in some scenarios, and Australia is the most sensitive region for the effects of greenhouse gas emissions. In addition to the uncertainty of ensemble prediction, the impacts of climate change on agriculture production and water resources are discussed as an extension of this research.

Implementation of a multisource model for gold nanoparticle‐mediated plasmonic heating with near‐infrared laser by the finite element method

The use of optically tunable gold nanoparticles (GNPs) in conjunction with near-infrared (NIR) laser has emerged as an attractive option for laser-induced thermal therapy (LITT), as it capitalizes on plasmonic heating of GNPs tuned to absorb light strongly in the NIR region. Previously, the authors developed a multisource model to predict the temperature change in a GNP-laden tissue-like medium illuminated by NIR laser and implemented it by a linear superposition (LS) method combining analytic and finite element method (FEM) solutions. While it is intuitive and straightforward, the LS approach might be somewhat cumbersome to implement for realistic LITT cases because it requires separate calculations of the temperature change due to individual GNP heat sources and the laser heat source. Therefore, the current investigation aimed to develop a simpler yet mathematically more elegant and computationally more efficient method solely based on FEM to implement the authors' multisource model. A multisource FEM model was developed to calculate the full spatiotemporal temperature distribution due to all heat sources (i.e., individual GNPs and the laser heat source) by solving the heat diffusion equation with multiple heat sources using FEM. This model was tested for its validity using two computational phantoms, a two-layer GNP-laden cylindrical phantom and a breast phantom with a GNP-laden microcavity. For comparison, the results for the two phantom cases were also obtained from the LS method. For the two-layer phantom case, the FEM approach resulted in a maximum temperature increase of 16.4 °C at a depth of 1.35 cm, 2.5 mm below the interface between the two layers, while the LS method produced a maximum temperature increase of 16.7 °C at a depth of 1.3 cm, 2 mm below the interface between the two layers. A comparison of the depth versus temperature changes obtained from the two approaches showed reasonably good agreement within 6%. In the breast phantom case, the LS results show a maximum temperature increase of 16.35 °C at a depth of 2.17 cm, 0.3 mm away from the center of the cavity in the direction closer to the laser. The FEM results show the same characteristics as those obtained via the LS method with a maximum temperature increase of 16.2 °C at a depth of 2.16 cm, 0.4 mm away from the center of the cavity in the direction closer to the laser. The two methods produced good agreement within 2% for the depth versus temperature distributions. The current multisource FEM model not only reproduced the results from the previous LS model, but also dramatically reduced computation time by 2 orders of magnitude, despite a generally more stringent requirement for computer memory. With further experimental validation, the FEM model can be used to predict the distinct plasmonic heating characteristics expected from NIR laser illumination of tissue-like media filled with GNPs, while offering the capability of handling heterogeneous spatial distribution of GNPs for realistic clinical cases.

3D-modelling of temperature gradients induced by electrical power dissipation in a 3-body Domen-type calorimeter for absorbed dose measurements

The effect of thermal gradients that appear in the core of a Domen-type absorbed-dose calorimeter during an electrical calibration run is revised using a finite element 3D-numerical analysis. The local thermal modelling, that is the method allowing for spatio-temporal distribution of temperature within the three bodies of the graphite calorimeter, combined with both a careful analysis on what really happens when a certain amount of electrical power is dissipated in a NTC heating thermistor and the consideration of heat loss through radiation from the surface of the calorimeter bodies, has led to results which are in agreement with those obtained from experimental measurements and reported in the literature.

Two-dimensional simulation of atmospheric pressure cold plasma jets in a needle-plane electrode configuration

The propagation mechanisms of atmospheric pressure cold plasma jets have recently attracted much attention. In this paper, by using a self-consistent two-dimensional plasma fluid model, we have investigated the propagation problems in the cold atmospheric pressure helium plasma jets that are surrounded by helium itself and thin dielectric tube, respectively. The spatio-temporal distributions of electron density, ionization rate, electrical field, and electron temperature were obtained. It is found that both the radius and the permittivity of dielectric tube have an impact on the discharge characteristics. A new method of improving the electron density and plasma jet size was also proposed.

TH-F-211-01: A Finite Element Method-Based Multisource Model for Near-Infrared Laser-Mediated Plasmonic Heating with Optically-Tunable Gold Nanoparticles

Purpose: To develop a computational model based on the finite element method (FEM) that can be used to predict spatiotemporal heat distributions for near-infrared (NIR) laser-based thermal imaging and therapy applications involving highly heterogeneous gold nanoparticle (GNP) distributions in tissue. Methods: The absorption of external light in tissue can be greatly enhanced with the use of GNPs tuned to strongly absorb in the NIR region. Previously, a multisource heat model was developed to compute temperature elevation due to plasmonic heat generation from individual GNPs, treating each GNP as an independent heat source. However, it was implemented by a ‘multi-step approach’, computing the temperature increase due to each individual GNP by Green's function method and that due to laser light by FEM via optical diffusion approximation, separately. In the current investigation, a ‘one-step’ approach was developed to compute the full spatiotemporal temperature distribution due to multiple heat sources all together by solving the weak-form of the heat equation using FEM. This approach was applied to predict temperature increase inside a GNP-filled cavity mimicking a small breast tumor within a breast gel phantom. For the purpose of comparison, calculations were also performed using a ‘multi-step approach’. Results: The results from the one-step approach matched those from the multi-step approach to within 1.2% along the central axis of the laser. Conclusions: A multisource heat model was successfully solved by FEM-based one-step approach. Computational results from the one-step approach were found identical to those from the multi-step approach. Both models showed great flexibility in handling any heterogeneous distribution of GNPs without requiring prior knowledge of the optical properties a GNP-filled medium. The proposed one-step approach will facilitate the prediction of temperature change within GNP-filled tissue during NIR laser-based clinical applications. This work was supported by DOD/BCRP, W81XWH-08-1-0686. DOD/BCRP, W81XWH-08-1-0686.

Automatic defect identification using thermal image analysis for online weld quality monitoring

Online weld-monitoring systems are being developed to reduce the cost and delays in detecting defects and rectifying welding parameters. It is known that variations (a) in arc positioning, (b) in heat input and (c) due to the presence of contaminants distinctly manifest as differences in the spatial and temporal surface temperature distributions.In this paper, it is demonstrated that (i) offset positioned thermal imaging of online TIG welding is a feasible non-destructive monitoring technique for detecting porosities in the AA2219 welding, (ii) spatio-temporal temperature distributions close to and in the vicinity of the weld pool can provide statistically distinct features in defect-free and defective weld regions, and (iii) thermal image-based assessment compares very favorably with post-weld radiography assessment for significant defect occurrence. Given the high frame rates and temperature resolution of currently available infrared cameras, it is believed that infrared thermography can be a practical weld-monitoring option capable of providing reliable assessment comparable to more elaborate off-line assessment.

Analysis of projected hydrological behavior of catchments based on signature indices

Abstract. To precisely map the changes in hydrologic response of catchments (e.g. water balance, reactivity or extremes), we need sensitive and interpretable indicators. In this study we defined nine hydrologically meaningful signature indices: five indices were sampled on the flow duration curve, four indices were closely linked to the distribution of event runoff coefficients. We applied these signature indices to the output from a hydrologic catchment model for three different catchments located in the Nahe basin (Western Germany) to detect differences in runoff behavior resulting from different meteorological input data. The models were driven by measured and simulated (COSMO-CLM) meteorological data. It could be shown that the application of signature indices is a very sensitive tool to assess differences in simulated runoff behavior resulting from climatic data sets of different sources. Specifically, the selected signature indices allow assessing changes in water balance, vertical water distribution, reactivity, seasonality and runoff generation. These indices showed that the hydrological model is very sensitive to biases in mean and spatio-temporal distribution of precipitation and temperature because it acts as a filter for the meteorological input. Besides model calibration and model structural deficits, we found that bias correction of temperature fields and further adjustment of bias correction of precipitation fields is absolutely essential. We conclude that signature indices can act as indirect "efficiency measures" or "similarity measures" for output from regional or local climate models.

Spatial-temporal analysis of water temperatures during spring in Lake Erhai, China: implications for fisheries

Lake Erhai is located in a low latitude, high altitude region in Yunnan province, China, and contains diverse endemic aquatic organisms. This study provides baseline information on the spatiotemporal water temperature distribution for examining the thermal environment for aquatic organisms in Lake Erhai. Temperature observation using temperature loggers was conducted from March to June 2009, covering the spawning period of most cyprinid fishes, the dominant taxonomic group of fish in the lake. During the daytime, the hourly average temperature was different between the surface and the bottom layer both in the littoral and pelagic zones; those differences disappeared during the nighttime, indicating nocturnal vertical water mixing. Daily average temperature, as well as intraday temperature variation, was negatively correlated with the site depth both in the surface and the bottom layers, suggesting that the littoral zone is warmer than the pelagic zone but less stable as a thermal habitat for aquatic species. Based on its geological location and depth, Lake Erhai could be classified as a polymictic lake, which tends to be well mixed; however, our study results indicate a high heterogeneity in water temperature. This specific thermal environment supports local fauna and flora and thus must be conserved to ensure their survival.

MR temperature imaging of nanoshell mediated laser ablation

Minimally invasive thermal therapy using high-power diode lasers is an active area of clinical research. Gold nanoshells (AuNS) can be tuned to absorb light in the range used for laser ablation and may facilitate more conformal tumor heating and sparing of normal tissue via enhanced tumor specific heating. This concept was investigated in a xenograft model of prostate cancer (PC-3) using MR temperature imaging (MRTI) in a 1.5T scanner to characterize the spatiotemporal temperature distribution resulting from nanoparticle mediated heating. Tumors with and without intravenously injected AuNS were exposed to an external laser tuned to 808 nm for 180 sec at 4 W/cm2 under real-time monitoring with proton resonance frequency shift based MRTI. Microscopy indicated that these nanoparticles (140–150 nm) accumulated passively in the tumor and remained close to the tumor microvasculature. MRTI measured a statistically significant (p < 0.001) increase in maximum temperature in the tumor cortex (mean = 21 ± 7°C) in +AuNS tumors versus control tumors. Analysis of the temperature maps helped demonstrate that the overall distribution of temperature within +AuNS tumors was demonstrably higher versus control, and resulted in damage visible on histopathology. This research demonstrates that passive uptake of intravenously injected AuNS in PC-3 xenografts converts the tumor vasculature into a potent heating source for nanoparticle mediated ablation at power levels which do not generate significant damage in normal tissue. When used in conjunction with MRTI, this has implications for development and validation of more conformal delivery of therapy for interstitial laser ablations.

Spatiotemporal Distribution of Nitrogen Rotational Temperature during Pulsed Discharge in Air

We have investigated the gas temperature during pulsed discharge. The gas temperature is one of the most important parameters for application of pulsed discharge in atmospheric gases. At atmospheric pressure gases, the gas temperature can be assumed equal to its rotational temperature. In the present work, the rotational temperature of the nitrogen molecules in a coaxial discharge reactor was obtained by synthesizing measured and calculated spectra. The emission spectrum was obtained from the second positive system of the nitrogen molecule due to the transition from the C3Πu state to the B3Πg state. As the result, rapidly increasing of the temperature (approximately 60 K) was observed at the boundary between the streamer and the glow-like discharge phases. In this paper, the spatial and the temporal dependences of the rotational temperature during pulsed discharge are reported.

Spatiotemporal Distribution of Nitrogen Rotational Temperature during Pulsed Discharge in Air

We have investigated the gas temperature during pulsed discharge. The gas temperature is one of the most important parameters for application of pulsed discharge in atmospheric gases. At atmospheric pressure gases, the gas temperature can be assumed equal to its rotational temperature. In the present work, the rotational temperature of the nitrogen molecules in a coaxial discharge reactor was obtained by synthesizing measured and calculated spectra. The emission spectrum was obtained from the second positive system of the nitrogen molecule due to the transition from the C3Πu state to the B3Πg state. As the result, rapidly increasing of the temperature (approximately 60 K) was observed at the boundary between the streamer and the glow-like discharge phases. In this paper, the spatial and the temporal dependences of the rotational temperature during pulsed discharge are reported.

On Source Coding for Distributed Temperature Sensing with Shift-Invariant Geometries

We study the source coding problem in sensor networks deployed to monitor the evolution of spatio-temporal temperature distributions. The sensors sample the temperature field, quantize the samples and transmit the encoded samples through digital channels to some central unit, which computes an estimate of the original temperature field. Our analysis is based on the heat kernel's spectral properties, which are induced by the physics of heat diffusion. We determine rate distortion functions for various source coding schemes. In particular, we compare centralized coding, independent coding, Berger-Tung coding, and predictive quantization.

Spatiotemporal Temperature Distribution and Cancer Cell Death in Response to Extracellular Hyperthermia Induced by Gold Nanorods

Plasmonic nanoparticles have shown promise in hyperthermic cancer therapy, both in vitro and in vivo. Previous reports have described hyperthermic ablation using targeted and nontargeted nanoparticles internalized by cancer cells, but most reports do not describe a theoretical analysis for determining optimal parameters. The focus of the current research was first to evaluate the spatiotemporal temperature distribution and cell death induced by extracellular hyperthermia in which gold nanorods (GNRs) were maintained in the dispersion outside human prostate cancer cells. The nanorod dispersion was irradiated with near-infrared (NIR) laser, and the spatiotemporal distribution of temperature was determined experimentally. This information was employed to develop and validate theoretical models of spatiotemporal temperature profiles for gold nanorod dispersions undergoing laser irradiation and the impact of the resulting heat generation on the viability of human prostate cancer cells. A cell injury/death model was then coupled to the heat transfer model to predict spatial and temporal variations in cell death and injury. The model predictions agreed well with experimental measurements of both temperature and cell death profiles. Finally, the model was extended to examine the impact of selective binding of gold nanorods to cancer cells compared to nonmalignant cells, coupled with a small change in cell injury activation energy. The impact of these relatively minor changes results in a dramatic change in the overall cell death rate. Taken together, extracellular hyperthermia using gold nanorods is a promising strategy, and tailoring the cellular binding efficacy of nanorods can result in varying therapeutic efficacies using this approach.

Photothermal Response of Tissue Phantoms Containing Multi-Walled Carbon Nanotubes

Inclusion of multi-walled carbon nanotubes (MWNTs) into tissue prior to laser therapy has the potential to enhance the selectivity and effectiveness of cancer therapy by providing greater and more controlled thermal deposition. The purpose of this study was to investigate the optical and thermal response of tissue representative phantoms containing MWNTs to optical radiation. Tissue representative phantoms 20 mm in diameter and 1 mm in thickness were created from sodium alginate. Following the inclusion of MWNTs (900 nm in length, 40-60 nm in diameter) in phantoms, the distribution of MWNTs was observed using transmission electron microscopy. A predominantly, evenly dispersed and randomly oriented distribution of MWNTs was observed with a rare presence of MWNT clustering or clumping. In order to characterize the response of MWNT inclusion on optical properties of phantoms, the transmittance and reflectance spectra of phantoms with and without MWNT inclusion were measured with a spectrophotometer over a wavelength range of 200-1400 nm. Inclusion of MWNTs in phantoms dramatically enhanced light absorption across the entire wavelength range as evidenced by a diminished transmittance and reflectance compared with phantoms without MWNTs. In order to evaluate the spatiotemporal temperature distribution associated with laser irradiation of phantoms with and without MWNTs, the temperature was measured at discrete radial distances from the center of the incident laser beam using thermocouples. The rate of temperature increase and peak temperature for phantoms containing MWNTs was much greater compared with phantoms without MWNTs at all measurement locations. In conclusion, MWNT inclusion in tissue phantoms increases the optical absorption and temperature elevation, which may enable more effective photothermal therapies of human disease utilizing lasers.