Surface Temperature Elevation Research Articles

The Effects of Climate Change on Maternal, Fetal and Neonatal Health: An in-Depth Review

The substantial elevation in atmospheric greenhouse gas levels is a consequence of human activities, resulting in a 1.1°C elevation in surface temperature as the worldwide average. The detrimental outcomes of this temperature rise encompass severe weather events, deterioration in food, water, and air quality, alongside an escalation in vector-borne infectious diseases and/or transmission risks. The mitigation and adaptation to climate change are pivotal factors for the survival of humanity in the midst of this existential crisis. Climate change exerts notable effects on maternal, fetal, and neonatal health, with women experiencing more adverse impacts compared to men. Pregnant women may face conditions such as hypertensive disorders like preeclampsia and eclampsia, gestational diabetes mellitus (GDM), variations in pregnancy duration, and mental health disorders. Fetal and newborn health can be affected, leading to results like preterm birth (<37 weeks of gestation), low birth weight (<2500 grams), congenital anomalies (including atrial septum issues), early membrane rupture (EMR), underdeveloped immune systems, intrauterine growth restriction (IUGR), and neonatal death. Effective interventions aimed at reducing heat-related risks should include health education on heat and heat increase risks for caregivers - other than parents - and clinicians responsible for childcare. Additionally, there is a need for improvements in cooling systems in healthcare facilities, fair enhancements in housing quality, and food systems. Focus should also be placed on nutrition and lifestyle counseling. Despite the growing attention to the influence of climate on human health, the risks associated with heat and other factors associated with climate for women, pregnant individuals, newborns, infants, and children are not sufficiently addressed. This review seeks to investigate the effects of climate change on maternal, fetal, and neonatal outcomes related to health based on existing literature.

Large‐scale deviations between realized and fundamental thermal niches in global seaweed distributions

AbstractAimClimate change has profound effects on species' distributions, and it is crucial to understand how well physiological limits correspond to distribution patterns to provide realistic estimations of future range shifts and/or extinctions. Seaweeds are foundation species of global coastal ecosystems, and sea surface temperature is a main predictor to explain their distributions and redistributions under global warming. We here test the hypothesis that, in contrast to other marine ectotherms, physiological knowledge of temperature niches is a weak predictor for seaweed distributions.LocationGlobal.Time PeriodPresent (1984–2019).TaxaSeaweeds.MethodsWe analysed the predictive power of physiological temperature limits to predict real‐world distributions in 126 globally distributed seaweed species with linear and generalized linear mixed models.ResultsIn 72% of the species, there was a difference of ≥|2|°C between the physiological and the realized thermal limits. Both, thermal underfilling (distributional thermal limits narrower than the physiological limits) and overfilling (distributional thermal limits wider than the physiological limits) were present. Thus, in only 28% of the species the physiological limits corresponded to the distributional limits. While heat‐tolerance is a significant predictor for upper distributional temperature limits, we found no relationship between cold‐tolerance and lower distributional temperature limits and the latter two seem to be independent.Main ConclusionsPhysiological thermal limits have limited predictive power for seaweed distributions and deviations may be large. Especially cold‐tolerances are a weak predictor, and forecasting of migrations under changing global conditions (e.g. towards the poles) will need special attention. This indicates that responses towards climate change might be highly variable between seaweed species and difficult to predict. Further, nearly 60% of the investigated species had populations which are close to or beyond their reported upper survival limits and are thus probably under threat of eradication by elevation of sea surface temperature.

Are there differences in the adaptive profile of hair sheep and their crosses with wool breeds?

This study aimed to evaluate and compare the physiological performance of different genetic groups of sheep, by physiological variables and serum hormone levels, in a hot weather environment. Thirty sheep from five genetic groups were used: Santa Inês (SI), ½ Dorper + ½ Santa Inês (DO), ½ Ilê de France + ½ Santa Inês (IF), ½ Suffolk + ½ Santa Inês (SK), and ½ Texel + ½ Santa Inês (TX). The readings and records of physiological parameters (respiratory rate (RR), rectal temperature (RT), auricular cavity temperature (ACT), and surface temperature (ST)) were carried out at 7:00 am, 1:00pm, and 7:00pm, in 12 non-consecutive days. The collections of blood samples for hormone analysis (triiodothyronine (T3), thyroxine (T4), and cortisol (CORT)) is in four consecutive days. The environmental conditions of the experimental period caused a thermal discomfort in the sheep, but not a state of thermal stress. The thermolysis mechanisms, sensitive (ST and ACT) and latent (RR) processes, were enough to maintain their homeostasis (RT). The results showed that crossbred breeds presented a higher metabolism and were more efficient at dissipating heat through thermolysis than the SI breed. The crossbred breeds were efficient at dissipating heat through the elevation of body surface temperature and respiratory rate, mainly SK and TX, i.e., crossbred breeds, despite the wool cover, used thermoregulatory mechanisms that promoted lower variation of RT. The analysis of variance showed significant effects (P < 0.05) to the time factor in the responses of T4 and T3, and to the breed factor in the responses of CORT, T4, and T3. We did not observe interaction between the factors to any of the hormonal variables. Therefore, we can state that the effect of time was independent of breed and vice versa. Thyroid hormones presented lower blood concentration in the mornings (4.03 ± 0.82, T4; 65.08 ± 10.6, T3), increasing their concentration in the afternoon (4.60 ± 1.03, T4; 70.16 ± 14.17, T3). The thyroid hormones presented a normal circadian rhythm, with the exception of SK. Air temperature (AT) showed greater correlation with physiological variables than enthalpy (H) did, in the experimental conditions. However, H showed correlation with T4 and T3. The adaptive profile of the genetic groups under study are different, but the IF genetic group showed better performance under environmental conditions.

Parameter variation effects on millimeter wave dosimetry based on precise skin thickness in real rats

This study presents a parametric analysis of the steady-state temperature elevation in rat skin models due to millimeter wave exposure at frequencies from 6–100 GHz. The statistical data of the thickness of skin layers, namely epidermis, dermis, dermal white adipose tissue, and panniculus carnosus, were measured for the first time using the excised tissues of real male Sprague–Dawley rats. Based on the precise structure obtained from the histological analysis of rat skin, we solve the bioheat transfer equation to investigate the effects of changes in parameters, such as body parts and thermal constants, on the absorbed power density and temperature elevation of biological tissues. Owing to the notably thin dermal white adipose tissue layer, the surface temperature elevation in the rat head and dorsal skin at 6–100 GHz is 52.6–32.3% and 83.3–58.8% of the average values of different human skin models, respectively. Our results also reveal that the surface temperature elevation of rat skin may correlate with the tissue thickness and deep blood perfusion rates.

Prediction of CO pollutant in Mashhad metropolis, Iran: Using multiple linear regression

AbstractGiven the importance of carbon monoxide (CO) in acute health threats, studies have been conducted in different countries and cities (272 cities in China and 337 cities on a global scale) on the relationship between daily mortality and CO while the spatial analysis of factors affecting CO pollutant in cities, especially in developing countries, has rarely been done. Accordingly, this research has measured the effect of five environmental‐social variables (ESVs) on the spatial distribution of CO pollutants in the metropolis of Mashhad, Iran. CO concentration data were collected in 23 air pollutant monitoring stations in an area of 356 km2 in 2019. Then, the relationship between five variables and CO pollutant were measured using linear and multiple regression by Sentinel 2A and 3 satellite images in ArcGIS and TerrSet software. The results show that the mean CO concentration averages at 1.56 ppm in the whole city. But its range varies between 0.171 and 2.907 ppm, which is a low figure compared with presented standards and does not indicate a critical situation. The results of multiple regression indicate that 42% of the variance in CO concentration is explained by independent variables. Among five independent variables, the beta value of the land surface temperature (LST) and digital elevation model (DEM) variables is negative and positive for the other three variables, including population density, normalised difference vegetation index (NDVI) and normalised difference built‐up index (NDBI). It should be noted that the strongest correlating variable is population density. Prediction of the spatial distribution of CO pollutants shows the division of the city into three areas: (1) the south and southwest slopes of the city with a low concentration; (2) central areas with a medium concentration; and (3) northern and northeastern areas of the city with a high concentration where low‐income groups reside and there are more worn‐out vehicles, motorcycles and industrial workshops. Areas with high CO concentration need more attention from urban managers.

一本歯サンダルを着用して行う足踏み運動が内側縦アーチ高と足底表面温度に与える影響

Single-tooth sandals under new development have special material and shape characteristics. Exercises with single-tooth sandals can increase pressing stimulus on the soles of the feet, thereby suppressing a decline in medial longitudinal arch and elevating sole surface temperature. This study thus aimed to examine the effects of exercise with single-tooth sandals on medial longitudinal arch and sole surface temperature. Sixteen young adults (23 ± 5 years) participated in 20 min of stepping exercise on the spot. They randomly put on a regular normal sandal (N conditions) or a single-tooth sandal (Z conditions) on each left and right side. Before and after exercise, medial longitudinal arch and sole surface temperature were assessed by digital caliper and straightedge and thermography, respectively. No significant differences in baseline parameters were observed between N and Z conditions. After exercise, arch height and arch height ratio significantly reduced in N conditions, but not in Z conditions. Central sole surface temperature in Z conditions also increased significantly, and the changes in surface temperature were significantly higher in Z conditions than in N conditions. Therefore, these findings suggest that exercise with single-tooth sandals has a positive effect on a suppressing decline in medial longitudinal arch and an elevation in sole surface temperature.

Thermal regulation of photovoltaics using various nano-enhanced phase change materials: An experimental study

Photovoltaics thermal (PV/T) management has attracted much attention in research, with a particular focus on improving its performance in the current globalized market. As the continuous elevation of PV surface temperature due to direct sun rays degrades PV/T performance, effective cooling of PV panels has been identified as a way of improving efficiency. Thermal regulation strategies have suggested that water, nanofluids, air, phase change materials (PCM), and nano-enhanced PCMs can be varied for cooling purposes. The current study considers silica and carbon black nanoparticles dispersed in phase change materials for two purposes: firstly, to increase the speed of storing and releasing thermal energy of nano-enhanced PCM; and secondly, for improving the thermal conductivity of PCM. The experimentation of this study was conducted in outdoor conditions of Taxila, Pakistan during the month of March 2020. To construct the nano-enhanced PCM, Silica (SiO2) and Carbon Black (CB) NPs were added to PT-58 at concentrations of 0.25 wt % and 0.5 wt %. NPs at 0.5 wt % concentration in CB/PT-58 as a nano-enhanced PCM showed the topmost performance in cooling of a PV panel. The experimentation depicted a maximum decrease in temperature of the system using CB/PT-58 and SiO2/PT-58, at approximately 9.74 °C and 8.92 °C respectively, where the electrical efficiency of the systems improved to 12.07% and 12.00% respectively, at a concentration of 0.5 wt %. The maximum percentage increment in electrical power was 30.45 % and 30.23 % respectively, in the case of CB/PT-58 and silica/PT-58 nano-PCM at 0.5 wt % of NPs in base PCM. The results elucidate that the performance of the system using the CB/PT-58 nano-PCM as a cooling method was higher than the silica/PT-58 nano-PCM.

Photothermal properties of aluminum oxide/Ag nanoparticles cermet-based coating synthesized by reactive magnetron co-sputtering

Cermet based-coatings, made of a ceramic matrix and metallic nanoparticles, have attracted a lot of attention in applications such as solar absorbers in a solar concentrating system since they allow a strong solar absorptance, a low IR emittance, and present good thermal stability. It has been shown that many parameters impact the performances of the cermet-based solar absorber such as the thickness, composition, and features of the metallic nanoparticles. In this study, we report on the synthesis of a Al2O3-Ag cermet by reactive co-sputtering of Ag and aluminum in Ar/O2 gas mixtures. The influence of important experimental parameters (i.e. sputtering power on the Ag target, deposition time, and O2 content) on the chemistry, morphology, and optical properties of the cermet coating is studied while the photothermal property of the cermet has been evaluated by measuring the surface elevation temperature of the coating under 1 sun irradiation. Our data reveal that by optimizing the features of the cermet, an absorbance of 0.92 and a surface temperature elevation up to 9.1 K can be reached after 30 min of illumination.

Towards an operational model for estimating day and night instantaneous near-surface air temperature for urban heat island studies: outline and assessment

Near-surface air temperature (NSAT) is key for assessing urban heat islands, human health, and well-being. However, a widely recognized and cost- and time-effective replicable approach for estimating hourly NSAT is still urgent. In this study, we outline and validate an easy-to-replicate, yet effective, operational model, for automating the estimation of high-resolution day and night instantaneous NSAT. The model is tested on a heat wave event and for a large geographical area. The model combines remotely sensed land surface temperature and digital elevation model, with air temperature from local fixed weather station networks. Achieved NSAT has daily and hourly frequency consistent with MODIS revisiting time. A geographically weighted regression method is employed, with exponential weighting found to be highly accurate for our purpose. A robust assessment of different methods, at different time slots, both day- and night-time, and during a heatwave event, is provided based on a cross-validation protocol. Four-time periods are modelled and tested, for two consecutive days, i.e. 31st of July 2020 at 10:40 and 21:50, and 1st of August 2020 at 02:00 and 13:10 local time. High R2 was found for all time slots, ranging from 0.82 to 0.88, with a bias close to 0, RMSE ranging from 1.45 °C to 1.77 °C, and MAE from 1.15 °C to 1.36 °C. Normalized RMSE and MAE are roughly 0.05 to 0.08. Overall, if compared to other recognized regression models, higher effectiveness is allowed also in terms of spatial autocorrelation of residuals, as well as in terms of model sensitivity.

Ice accretion thickness prediction using flash infrared thermal imaging and BP neural networks

The present study investigated ice accretion thickness under non-incoming flow icing conditions on the ground using an infrared thermography system that converts infrared radiation temperature. Two back propagation (BP) neural network models were developed to measure ice thickness. Both theoretical model and polynomials were employed to fit the icing surface temperature elevation sequence to extract the pixel-level temperature attenuation characteristics, which were served as the input to the BP neural networks. The prediction method of ice thickness by the BP neural network was analysed from three perspectives of sensitivity, dimension, and precision. In addition, K-nearest neighbour (KNN) and support vector regression (SVR) algorithms were compared with BP neural network. In terms of prediction effect, the BP neural network performed the best. The verification of the BP neural network based on the characteristics of the theoretical model proved that the method can effectively predict the thickness of ice accretion, and its prediction error does not exceed 10%.

Study on air temperature estimation and its influencing factors in a complex mountainous area

Near-surface air temperature (Ta) is an important parameter in agricultural production and climate change. Satellite remote sensing data provide an effective way to estimate regional-scale air temperature. Therefore, taking Gansu section of the upper Weihe River Basin as the study area, using the filtered reconstructed high-quality long-time series normalized difference vegetation index (NDVI), interpolated reconstructed land surface temperature (LST), surface albedo, and digital elevation model (DEM) as the input data, the back-propagation artificial neural network algorithm (BP-ANN) was combined with a multiple linear regression method to estimate regional air temperature, and the influencing factors of air temperature estimation were analyzed. This method effectively compensates for the fact that air temperature data provided by a single station cannot represent regional air temperature information. The result shows that the temperature estimation accuracy is high. In terms of interannual variation, the air temperature in the study area showed a slightly increasing trend, with an average annual increase of 0.047°C. The calculation results of the interannual variation rate of temperature showed that the area with increased air temperature accounted for 75.8% of the total area. In terms of seasonal variation, compared with that in summer and winter, the air temperature rising trend in autumn was obvious, and the air temperature in the middle of the study area decreased in spring, which is prone to frost disasters. LST and NDVI in the study area were positively correlated with air temperature, and their positive correlation distribution areas accounted for 93.62% and 94.34% of the total study area, respectively. NDVI, LST and DEM influence the temperature change in the study area. The results show that there is a significant positive correlation between NDVI and air temperature, and the change of NDVI has a positive effect on the spatiotemporal variation of air temperature. The correlation coefficient between LST and air temperature in the southeast of the study area is negative, and there is a difference. In addition, the correlation coefficient between LST and air temperature in other areas of the study area is positive. The air temperature decreased with elevation, air temperature decreases by 0.27°C every hundred meters.

No general stability conditions for marine ice-sheet grounding lines in the presence of feedbacks

The “marine ice-sheet instability” hypothesis continues to be used to interpret the observed mass loss from the Antarctic and Greenland ice sheets. This hypothesis has been developed for conditions that do not account for feedbacks between ice sheets and environmental conditions. However, snow accumulation and the ice-sheet surface melting depend on the surface temperature, which is a strong function of elevation. Consequently, there is a feedback between precipitation, atmospheric surface temperature and ice-sheet surface elevation. Here, we investigate stability conditions of a marine-based ice sheet in the presence of such a feedback. Our results show that no general stability condition similar to one associated with the “marine ice-sheet instability” hypothesis can be determined. Stability of individual configurations can be established only on a case-by-case basis. These results apply to a wide range of feedbacks between marine ice sheets and atmosphere, ocean and lithosphere.

Design of a Skin Equivalent Phantom for Estimating Surface Temperature Elevation Due to Human Exposure to Electromagnetic Fields From 10 to 100 GHz

A semisolid human-body phantom for simulating the steady-state temperature elevation at the skin surface due to exposure to millimeter waves (MMWs) and quasi-MMWs was developed in this article. The phantom was designed by optimizing the electric constants of a mixed material consisting mainly of water and glycerin. First, the empirical equation of the complex permittivity of the phantom with respect to the composition and frequency was derived from dielectric measurements of phantoms. Then, the phantom composition used to obtain the temperature elevation equivalent to skin exposure were optimized using a computational approach. Here, the phantom composition was optimized at frequencies ranging from 10 to 100 GHz. In addition, we found that a single composition can be used for frequencies from 20 to 100 GHz. This phantom can simulate the temperature elevation due to skin exposure within the variation of the temperature elevation due to the individual differences in human tissue thickness. The developed phantom was validated by thermographic measurement using a horn antenna and an array antenna at 28 and 60 GHz, respectively. The developed phantoms are applicable to the thermal assessment of skin exposure to electromagnetic fields at MMW and quasi-MMW frequencies.

Effect of the Spatial Distribution of the Temperature and Humidity Index in a New Zealand White Rabbit House on Respiratory Frequency and Ear Surface Temperature.

Simple SummaryA rabbit house’s microclimate has a strong influence on the physiological responses of rabbits, and thermal discomfort may damage their development. The primary aim of this study was to develop a spatial distribution of temperature and humidity index (THI) maps via kriging interpolation, as well as to characterize and evaluate its relationship with physiological responses (i.e., the respiratory frequency (RF) and ear surface temperature (EST) of New Zealand white (NZW) rabbits kept in a rabbit house. The spatial distribution maps of THI allowed us to visualize the heterogeneity in the distribution space of the variables, as well as to identify regions where NZW rabbits were exposed to unfavorable developmental conditions. The relationship between THI, RF, and EST was evident, and the maps showed that an increase in THI led to an acceleration of respiratory movements and an elevation of surface temperature in rabbit ears. This led to an attempt to dissipate excess heat acquired from the environment. Thus, the spatial distribution maps of THI overlaid with RF and EST data was found to provide useful information to assist the producer in making decisions to improve the production environment for NZW rabbits.The objective of this study was to characterize and evaluate the temperature and humidity index (THI) of New Zealand white (NZW) rabbits kept in a rabbit house using geostatistical techniques. Furthermore, we sought to evaluate its relationship with respiratory frequency (RF) and ear surface temperature (EST). The experiment was conducted at the Federal University of Lavras, Brazil. A total of 52 NZW rabbits were used. For the characterization of the thermal environment, the dry bulb temperature (tdb, °C), relative humidity (RH, %), and dew point temperature (tdp, °C) were collected at 48 points in the rabbit house at 6:00 a.m., 12:00 p.m., and 6:00 p.m. for seven days. The RF and EST of the animals was monitored. Subsequently, the THI was calculated and the data were analyzed using geostatistical tools and kriging interpolation. In addition, the RF and EST data were superimposed on the rabbit house’s THI data maps. The magnitude of the variability and structure of the THI inside the rabbit house were characterized and the heterogeneity was visualized. Critical THI points inside the rabbit house and in locations where animals with high RF and ESTs were housed were identified, thus providing information about improving the production environment.

Thermographic imaging of mouse across circadian time reveals body surface temperature elevation associated with non-locomotor body movements.

Circadian clocks orchestrate multiple different physiological rhythms in a well-synchronized manner. However, how these separate rhythms are interconnected is not exactly understood. Here, we developed a method that allows for the real-time simultaneous measurement of locomotor activity and body temperature of mice using infrared video camera imaging. As expected from the literature, temporal profiles of body temperature and locomotor activity were positively correlated with each other. Basically, body temperatures were high when animals were in locomotion. However, interestingly, increases in body temperature were not always associated with the appearance of locomotor activity. Video imaging revealed that mice exhibit non-locomotor activities such as grooming and postural adjustments, which alone induce considerable elevation of body temperature. Noticeably, non-locomotor movements always preceded the initiation of locomotor activity. Nevertheless, non-locomotor movements were not always accompanied by locomotor movements, suggesting that non-locomotor movements provide a mechanism of thermoregulation independent of locomotor activity. In addition, in the current study, we also report the development of a machine learning-based recording method for the detection of circadian feeding and drinking behaviors of mice. Our data illustrate the potential utility of thermal video imaging in the investigation of different physiological rhythms.

SPATIAL AND TEMPORAL VARIABILITY OF SURFACE TEMPERATURE, LAND USE AND LAND COVER CHANGE: A CASE STUDY IN CAMPINAS, BRAZIL

deteriorating climatic conditions in urban centers of Brazil is a real concern for human security and urban livelihood sustainability. The city of Campinas in São Paulo state/Brazil is highly vulnerable to climatic disasters. The present paper analyses the relationship between land use changes and temperature in Campinas between 1989 and 2016. The 28-year period was chosen due to the variability of climatic data in three meteorological stations (University of Campinas, Agronomic Institute of Campinas and International Airport of Viracopos). Data from five sources were used for land use land changes (LULC), and land surface temperature (LST) analysis. The data sources were: i) Landsat 5 Thermometer Mapper (TM), ii) Landsat 5 Thermal Infrared Sensor (TIRS), iii) Thermal Infrared Sensor (ETM +) sensors from Landsat 5, iv) Landsat 8 Operational Land Imager (OLI), and v) Thermal Infrared Sensor (TIRS). The results indicate consistent relations between urbanized increase area and the elevation of air and surface temperature in Campinas. In the studied period, there was an increase of 23% in urbanized areas in Campinas and around the meteorological stations. Cepagri presented the highest growth, about 22%, as well as the station with the highest air temperature

Comparison and assessment of spatial downscaling methods for enhancing the accuracy of satellite-based precipitation over Lake Urmia Basin

Estimating precipitation at high spatial-temporal resolution is vital in manifold hydrological, meteorological and water management applications, especially over areas with un-gauged networks and regions where water resources are on the wane. This study aims to evaluate five downscaling methods to determine the accuracy and efficiency of which on generating high-resolution precipitation data at annual and monthly scales. To establish precipitation-Land surface characteristics relationship, environmental factors, including Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST) and Digital Elevation Model (DEM), were considered as proxies in the spatial downscaling procedure. The downscaling algorithms, namely support vector machine (SVM), random forest (RF), geographically weighted regression (GWR), multiple linear regression (MLR) and exponential regression (ER), were implemented to downscale the version 7 of TRMM (Tropical Rainfall Measuring Mission) precipitation (3B43 V7 product) over Lake Urmia Basin (LUB) from 0.25° to 1 km spatial resolution. The downscaled precipitation data was validated against observations from meteorological stations. Monthly fractions derived from TRMM 3B43 were used to disaggregate 1 km annual precipitation to 1 km monthly precipitation. Furthermore, the best method was selected for calibration based on Geographical Difference Analysis (GDA) to assess the effectiveness of the calibration as a viable option. The results indicate that SVM not only outperforms the other methods, but also has good agreements with in-situ measurements compared to the original TRMM. The results confirm that inclusion of LST and geographic information along with NDVI can improve the downscaling performance. Downscaling and GDA calibration significantly improve the accuracy of TRMM 3B43 product at both spatial and temporal resolution and should be considered as an essential step in calibration of TRMM precipitation. Calibration at monthly scale yields slightly better results than calibration at annual scale and then disaggregating into monthly maps in terms of accuracy assessment.

Numerical Analysis of Electromagnetic Field Exposure from 5G Mobile Communications at 28 GHZ in Adults and Children Users for Real-World Exposure Scenarios.

The recent development of millimeter-wave (mmW) technologies, such as the fifth-generation (5G) network, comes with concerns related to user exposure. A quite large number of dosimetry studies above 6 GHz have been conducted, with the main purpose being to establish the correlation between different dosimetric parameters and the skin surface temperature elevation. However, the dosimetric studies from 28 GHz user equipment using different voxel models have not been comprehensively discussed yet. In this study, we used the finite-difference time-domain (FDTD) method for the estimation of the absorption of radiofrequency (RF) energy from a microstrip patch antenna array (28 GHz) in different human models. Specifically, we analyzed different exposure conditions simulating three real common scenarios (a phone call scenario, message writing scenario, and browsing scenario) regarding the use of smartphones/tablets by four different individuals (adult male and female, child male and female). From the results of Absorbed Power Density (Sab), it is possible to conclude that all the considered exposure scenarios comply with the safety limits, both for adult and children models. However, the high values of the local Specific Absorption Rate (SAR) in the superficial tissues and the slight differences in its distribution between adults and children suggest the need for further and more detailed analysis.

25-Hydroxyvitamin D Deficiency: Impacting Deep-Wound Infection and Poor Healing Outcomes in Patients With Diabetes

The Kingdom of Bahrain has a high incidence of diabetes and associated foot complications. Simultaneously, low 25-hydroxyvitamin D (25[OH]D) levels are common in this population and may be associated with the traditional clothing used in desert climates. This investigation compared 25(OH)D levels and glycemic control with quantifiable wound healing parameters in a prospective, analytic, nonexperimental, cross-sectional pilot study. Consecutive consenting adult patients (N = 80) who presented to the regional wound care unit in January 2016 with either an existing or new wound were included. Collected data included three-dimensional wound photography, NERDS and STONEES criteria, and an X-ray with a positive probe-to-bone test. Blood values for 25(OH)D and hemoglobin A1c (HbA1c) were collected simultaneously. Diabetes mellitus (types 1 and 2) was present in 90% of the sample patients. No patient had sufficient 25(OH)D levels; 15% had insufficient levels (30-50 ng/mL), and deficiency (levels <#20 ng/mL) was found in 85% of the sample. Males were slightly less affected by 25(OH)D deficiency compared with females (82.4% vs 91.3%). Poor glycemic control (HbA1c levels >#6.8%) was found in 69.4% (n = 50) of the persons with diabetes included in the sample. Those with both diabetes mellitus and a 25(OH)D deficiency (76.3%; n = 61) were more likely to demonstrate healing difficulty (40.9%; n = 25) or present with a stalled or deteriorating wound (44.2%, n = 27). A 3° F or higher periwound surface temperature elevation over a mirror image site was present in 82.5% of all wounds. Exposed bone in the ulcer base was found in 50% of the cases. For persons with diabetes, general linear modeling statistical analysis (adjusted R value = 47.9%) linked poor wound healing with three studied variables: 25(OH)D deficiency, poor glycemic control, and an exposed bone in the wound bed. Vitamin D may be an overlooked factor in the pathophysiology of diabetic foot ulcer development and subsequent delay in wound healing outcomes. The authors recommend adding 25(OH)D deficiency to the list of multifactorial aggravating factors providers should consider correcting in this subgroup of patients.

End-of-season senescence in grassland species can be traced to leaf temperature during preceding summer drought

In natural multi-species communities, drought extremes elicit complex, though seldom measured, ecophysiological responses triggered by divergent drought coping strategies and plant-plant interactions. This raises the question whether the whole-season impact of such events is in any way predictable in such systems from stress measurements during the drought. Here, we experimentally induce local variation in soil moisture in a humid, multi-species, temperate grassland in summer and test whether any of the stress indicators (stomatal conductance, net photosynthetic rate and midday leaf surface temperature) measured on the seven most abundant species is a good early warning signal of end-of-season senescence. We found that, across species, plants exposed to lower soil water content experienced similar elevation of leaf surface temperature, and that plants with warmer leaves during the drought extreme were consistently more senescent at the end of the growing season two months later, averaging 0.7% surplus leaf senescence with every additional 1 °C. We also observed links between lagged effects in the weeks after the drought, which were weakly negative on stomatal conductance, but strongly positive on photosynthesis in some species, and end-of-season senescence. Part of the damage might thus be ascribed to these drought legacies. To conclude, even in complex field settings, local leaf surface temperature measured at an early stage can be a powerful and species-specific indicator of the whole-season impact of drought extremes. This opens perspectives to estimate where in the landscape such events will be most detrimental.