Efficient Electromagnetic Wave Absorption and Thermal Infrared Stealth in PVTMS@MWCNT Nano‑Aerogel via Abundant Nano‑Sized Cavities and Attenuation Interfaces

Pre-polymerized vinyl trimethoxy silane(PVTMS)@MWCNT nano-aerogel system was constructed via radical polymerization,sol-gel transition and supercritical CO_(2)drying.The fabricated organic-inorganic hybrid PVTMS@MWCNT aerogel structure shows nano-pore size(30-40 nm),high specific surface area(559 m^(2)g^(−1)),high void fraction(91.7%)and enhanced mechanical property:(1)the nano-pore size is beneficial for efficiently blocking thermal conduction and thermal convection via Knudsen effect(beneficial for infrared(IR)stealth);(2)the heterogeneous interface was beneficial for IR reflection(beneficial for IR stealth)and MWCNT polarization loss(beneficial for electromagnetic wave(EMW)attenuation);(3)the high void fraction was beneficial for enhancing thermal insulation(beneficial for IR stealth)and EMW impedance match(beneficial for EMW attenuation).Guided by the above theoretical design strategy,PVTMS@MWCNT nano-aerogel shows superior EMW absorption property(cover all Ku-band)and thermal IR stealth property(ΔT reached 60.7℃).Followed by a facial combination of the above nano-aerogel with graphene film of high electrical conductivity,an extremely high electromagnetic interference shielding material(66.5 dB,2.06 mm thickness)with superior absorption performance of an average absorption-to-reflection(A/R)coefficient ratio of 25.4 and a low reflection bandwidth of 4.1 GHz(A/R ratio more than 10)was experimentally obtained in this work.

Sea ice thickness analyses for the Bohai Sea using MODIS thermal infrared imagery

Level ice thickness distribution pattern in the Bohai Sea in the winter of 2009-2010 was investigated in this paper using MODIS night-time thermal infrared imagery. The cloud cover in the imagery was masked out manually. Level ice thickness was calculated using MODIS ice surface temperature and an ice surface heat balance equation. Weather forcing data was from the European Centre for Medium-Range Weather Forecasts （ECMWF） analyses. The retrieved ice thickness agreed reasonable well with in situ observations from two off-shore oil platforms. The overall bias and the root mean square error of the MODIS ice thickness are -1.4 cm and 3.9 cm, respectively. The MODIS results under cold conditions （air temperature 〈 -10~C） also agree with the estimated ice growth from Lebedev and Zubov models. The MODIS ice thickness is sensitive to the changes of the sea ice and air temperature, in particular when the sea ice is relatively thin. It is less sensitive to the wind speed. Our method is feasible for the Bohai Sea operational ice thickness analyses during cold freezing seasons.

Utilization of Thermal Infrared Image for Inversion of Winter Wheat Yield and Biomass

The present paper utilizes thermal infrared image for inversion of winter wheat yield and biomass with different technology of irrigation(drip irrigation,sprinkler irrigation,flood irrigation).It is the first time that thermal infrared image is used for predicting the winter wheat yield and biomass.The temperature of crop and background was measured by thermal infrared image.It is necessary to get the crop background separation index(CBSIL,CBSIH),which can be used for distinguishing the crop value from the image.CBSIL and CBSIH(the temperature when the leaves are wet adequately;the temperature when the stomata of leaf is closed completely) are the threshold values.The temperature of crop ranged from CBSIL to CBSIH.Then the ICWSI was calculated based on relevant theoretical method.The value of stomata leaf has strong negative correlation with ICWSI proving the reliable value of ICWSI.In order to construct the high accuracy simulation model,the samples were divided into two parts.One was used for constructing the simulation model,the other for checking the accuracy of the model.Such result of the model was concluded as:(1) As for the simulation model of soil moisture,the correlation coefficient(R2) is larger than 0.887 6,the average of relative error(Er) ranges from 13.33% to 16.88%;(2) As for the simulation model of winter wheat yield,drip irrigation(0.887 6,16.89%,-0.12),sprinkler irrigation(0.970 0,14.85%,-0.12),flood irrigation(0.969 0,18.87%,0.18),with the values of R2,Er and CRM listed in the parentheses followed by the individual term.(3) As for winter wheat biomass,drip irrigation(0.980 0,13.70%,0.13),sprinkler irrigation(0.95,13.15%,-0.14),flood irrigation(0.970 0,14.48%,-0.13),and the values in the parentheses are demonstrated the same as above.Both the CRM and Er are shown to be very low values,which points to the accuracy and reliability of the model investigated.The accuracy of model is high and reliable.The results indicated that thermal infrared image can be used potentially for inversion of winter wheat yield and biomass.

Satellite Thermal Infrared Earthquake Precursor to the Wenchuan M_s 8.0 Earthquake in Sichuan,China,and its Analysis on Geo-dynamics

Based on an interpretation and study of the satellite remote-sensing images of FY-2C thermal infrared 1st wave band （10.3-11.3 μm） designed in China, the authors found that there existed obvious and isolated satellite thermal infrared anomalies before the 5.12 Wenchuan Ms 8.0 Earthquake. These anomalies had the following characteristics： （1） The precursor appeared rather early： on March 18, 2008, i.e., 55 days before the earthquake, thermal infrared anomalies began to occur; （2） The anomalies experienced quite many and complex evolutionary stages： the satellite thermal infrared anomalies might be divided into five stages, whose manifestations were somewhat different from each other. The existence of so many anomaly stages was probably observed for the first time in numerous cases of satellite thermal infrared research on earthquakes; （3） Each stage lasted quite a long time, with the longest one spanning 13 days; （4） An evident geothermal anomaly gradient was distributed along the Longmen seismic fracture zone, and such a phenomenon might also be discovered for the first time in satellite thermal infrared earthquake research. This discovery is therefore of great guiding and instructive significance in the study of the earthquake occurrence itself and the trend of the postearthquake phenomena.

Modeling co-seismic thermal infrared brightness anomalies in petroliferous basins surrounding the North and East of the Qinghai–Tibet Plateau

Co-seismic gas leakage usually occurs on the edge of seismic faults in petroliferous basins,and it may have an impact on the local environment,such as the greenhouse effect,which can cause thermal infrared brightness anomalies.Using wavelet transform and power spectrum estimation methods,we processed brightness temperature data from the Chinese geostationary meteorological satellite FY-C/E.We report similarities between the co-seismic thermal infrared brightness(CTIB)anomalies before,during and after earthquakes that occurred at the edges of the Sichuan,Tarim,Qaidam,and Junggar basins surrounding the North and East of the Qinghai–Tibet Plateau in western China.Additionally,in each petroliferous basin,the area of a single CTIB anomaly accounted for 50%to 100%of the basin area,and the spatial distribution similarities in the CTIB anomalies existed before,during and after these earthquakes.To better interpret the similarities,we developed a basin warming effect model based on geological structures and topography.The model suggests that in a petroliferous basin with a subsurface gas reservoir,gas leakage could strengthen with the increasing stress before,during,and even after an earthquake.The accumulation of these gases,such as the greenhouse gases CH4 and CO2,results in the CTIB anomalies.In addition,we conclude that the CTIB anomalies are strengthened by the high mountains(altitude^5000 m)around the basins and the basins’independent climatic conditions.This work provides a new perspective from which to understand the CTIB anomalies in petroliferous basins surrounding the North and East of the Qinghai–Tibet Plateau.

Probable satellite thermal infrared anomaly before the Zhangbei M_s=6.2 earthquake on January 10, 1998

This paper used the thermal infrared data of the satellite NOAA-AAVHRR of the north pat of North China (113°~119°E, 38°~42°N), and processed the remote sensing data through radiation adjustment, geometric adjust ment and so on by the software 'The Monitoring and Fast Process System of Earthquake Precursor Thermal Infra red Anomaly', inversed the each surface temperature. Some disturbances effect had been excluded, and thermal infrared temperature anomaly had been extracted by the picture difference method. The Zhangbei M_s=6.2 earth quake is used as the example in the paper, so that in the paper thermal infrared characteristics on time-space before earthquake and the relationship between the anomaly and the earthquake prediction have been summarized. Within more than ten days before the Zhangbei earthquake, the thermal infrared anomaly had emerged widely along Zhangjiakou-Bobal seismic belt, and the anomalous region seemed like a belt and it is also consistent with the tectonic background there; the anomaly expanded from the outside toward the earthquake focus, but the focus lay at the edge of the thermal infrared region. So it is possible to explore a new anomaly observation method for earthquake prediction by observing and studying the satellite thermal infrared anomaly before big earthquakes happen.

Formation cause of thermal infrared high temperature belt along Honghe fault and its relation to earthquakes

Aiming at two Dayao earthquakes with magnitude more than 6 occurred in 2003 in Yunnan Province, we analyzed and interpreted the NOAA satellite thermal infrared images of 1999, 2003 and 2004 in Chuandian region, and also calculated the annual variation of brightness temperature of the hot belt along Honghe fault to explore the formation cause of the high temperature belt and its relation to the earthquakes. The results show that the high temperature belt along Honghe fault is caused by geographic environment factors, such as water system and terrain. But the annual average brightness temperature of the belt in earthquake year of 2003 is clearly higher than that in no earthquake years of 1999 and 2004, this maybe indicates that the thermal activities of Honghe fault increase in earthquake years, and can cause the annual variation anomaly of brightness temperature. We can detect and monitor this thermal activities of Honghe fault before earthquake by analyzing and comparing the relative changes of thermal infrared brightness temperature of the hot belt in different years.

Gait Recognition System in Thermal Infrared Night Imaging by Using Deep Convolutional Neural Networks

Gait is an essential biomedical feature that distinguishes individuals through walking.This feature automatically stimulates the need for remote human recognition in security-sensitive visual monitoring applications.However,there is still a lack of sufficient accuracy of gait recognition at night,in addition to taking some critical factors that affect the performances of the recognition algorithm.Therefore,a novel approach is proposed to automatically identify individuals from thermal infrared(TIR)images according to their gaits captured at night.This approach uses a new night gait network(NGaitNet)based on similarity deep convolutional neural networks(CNNs)method to enhance gait recognition at night.First,the TIR image is represented via personal movements and enhanced body skeleton segments.Then,the state-space method with a Hough transform is used to extract gait features to obtain skeletal joints′angles.These features are trained to identify the most discriminating gait patterns that indicate a change in human identity.To verify the proposed method,the experimental results are performed by using learning and validation curves via being connected by the Visdom website.The proposed thermal infrared imaging night gait recognition(TIRNGaitNet)approach has achieved the highest gait recognition accuracy rates(99.5%,97.0%),especially under normal walking conditions on the Chinese Academy of Sciences Institute of Automation infrared night gait dataset(CASIA C)and Donghua University thermal infrared night gait database(DHU night gait dataset).On the same dataset,the results of the TIRNGaitNet approach provide the record scores of(98.0%,87.0%)under the slow walking condition and(94.0%,86.0%)for the quick walking condition.

Evaluation of facial temperature distribution changes during meditation using infrared thermal imaging:An experimental,cross-over study

Objective:To investigate the differences between meditation and resting states using infrared thermal imaging(IRTI)to determine facial temperature distribution features during meditation and annotate the patterns of facial temperature changes during meditation from the perspective of traditional Chinese medicine facial diagnosis.Methods:Each participant performed 10 min meditation and 10 min resting but in different sequences.A concentration test was set as the task load,followed by a meditation/resting or resting/meditation session,during which the participants'facial temperatures were observed using IRTI.Participants were scored on the Big Five Inventory(BFI)and Mindful Attention Awareness Scale(MAAS).Results:Forehead temperatures decreased more during meditation than during the resting state.The chin temperature increased only during meditation(P<.0001).For the subjects with meditation experience,there were significant differences in the temperatures of the left forehead(P<.01),right forehead(P<.01)and chin(P<.05)between the meditation and resting state at the 10~(th)min.In the nontask state,the BFI-Extraversion showed a negative correlation with the temperature of the left forehead(R=-0.41,P=.03).In the post-task state,the temperature of the left forehead was negatively correlated with scores on the MAAS(R=-0.42,P=.02).Conclusion:Using IRTI to study meditation offers a practical solution to the challenges in meditation research.The results indicate that an increase in chin temperature may be a representative feature of a meditation state,and forehead temperature is also a potential indicator.

Heat transfer and temperature evolution in underground mininginduced overburden fracture and ground fissures: Optimal time window of UAV infrared monitoring

Heat transfer and temperature evolution in overburden fracture and ground fissures are one of the essential topics for the identification of ground fissures via unmanned aerial vehicle(UAV) infrared imager. In this study, discrete element software UDEC was employed to investigate the overburden fracture field under different mining conditions. Multiphysics software COMSOL were employed to investigate heat transfer and temperature evolution of overburden fracture and ground fissures under the influence of mining condition, fissure depth, fissure width, and month alternation. The UAV infrared field measurements also provided a calibration for numerical simulation. The results showed that for ground fissures connected to underground goaf(Fissure Ⅰ), the temperature difference increased with larger mining height and shallow buried depth. In addition, Fissure Ⅰ located in the boundary of the goaf have a greater temperature difference and is easier to be identified than fissures located above the mining goaf. For ground fissures having no connection to underground goaf(Fissure Ⅱ), the heat transfer is affected by the internal resistance of the overlying strata fracture when the depth of Fissure Ⅱ is greater than10 m, the temperature of Fissure Ⅱ gradually equals to the ground temperature as the fissures’ depth increases, and the fissures are difficult to be identified. The identification effect is most obvious for fissures larger than 16 cm under the same depth. In spring and summer, UAV infrared identification of mining fissures should be carried out during nighttime. This study provides the basis for the optimal time and season for the UAV infrared identification of different types of mining ground fissures.

Emotion recognition from thermal infrared images using deep Boltzmann machine

Facial expression and emotion recognition from thermal infrared images has attracted more and more attentions in recent years. However, the features adopted in current work are either temperature statistical parameters extracted from the facial regions of interest or several hand-crafted features that are commonly used in visible spectrum. Till now there are no image features specially designed for thermal infrared images. In this paper, we propose using the deep Boltzmann machine to learn thermal features for emotion recognition from thermal infrared facial images. First, the face is located and normalized from the thermal infrared im- ages. Then, a deep Boltzmann machine model composed of two layers is trained. The parameters of the deep Boltzmann machine model are further fine-tuned for emotion recognition after pre-tralning of feature learning. Comparative experimental results on the NVIE database demonstrate that our approach outperforms other approaches using temperature statistic features or hand-crafted features borrowed from visible domain. The learned features from the forehead, eye, and mouth are more effective for discriminating valence dimension of emotion than other facial areas. In addition, our study shows that adding unlabeled data from other database during training can also improve feature learning performance.

Evaluating Infrared Thermal Image’s Color Palettes in Hot Tropical Area

The use of Infrared Thermal Scanners proved to be very useful in lots of applications. Using different color palettes, temperatures can be well-represented in the resulting image. However, most color palettes in hot tropical places like the Philippines are unsuitable since the ambient temperature is almost the same as the scanned object or person. This study evaluates twelve (12) known and used color palettes in the market to determine the most suitable for tropical places using the edge/border tracing algorithms Sobel-Feldman and Laplacian. The result shows that color palettes with the most colors produce more noise, making it difficult to distinguish the object scanned from the background. On the other hand, color palettes with three or fewer contrasting colors produce crisp and more detailed results. This study helps developers and researchers efficiently use color combinations suitable for hot weather for an effective thermal scanning and image representation.

Using thermal remote sensing in the classification of mountain permafrost landscapes

Thermal infrared satellite imagery is increasingly utilized in permafrost studies.One useful application of the land surface temperature(LST)products is classification and mapping of landscapes in permafrost regions,as LST values can help differentiate between frozen and unfrozen ground.This article describes a new approach to the use of LST.The essence of the new approach lies in the fact that in the territory where it is impossible to determine(indicate)the state of the underlying ground according to the same morphological characteristics(relief,vegetation,soil composition,etc.),the LST parameter,which reflects the thermal state of the landscape,allows as an additional criterion(indicator)identify frozen/un-frozen landscapes.In this work,using the above approach,a map has been compiled,which shows the permafrost natural-territorial complexes of the Elkon Massif,Eastern Siberia,including topography,slope aspect,slope angle,vegetation,snow cover and LST.The map provides a more detailed and updated description of permafrost distribution in the study area.

Experimental study on the infrared precursor characteristics of gas-bearing coal failure under loading

The stress and gas pressure in deep coal seams are very high,and instability and failure rapidly and intensely occur.It is important to study the infrared precursor characteristics of gas-bearing coal instability and failure.In this paper,a self-developed stress-gas coupling failure infrared experimental system was used to analyse the infrared radiation temperature(IRT)and infrared thermal image precursor characteristics of gas-free coal and gas-bearing coal.The changes in the areas of the infrared temperature anomalous precursor regions and the effect of the gas on the infrared precursors were examined.The results show that high-temperature anomalous precursors arise mainly when the gas-free coal fails under loading,whereas the gas-bearing coal has high-temperature and low-temperature anomalous precursors.The area of the high-temperature anomalous precursor is approximately 30%–40%under gasbearing coal unstable failure,which is lower than the 60%–70%of the gas-free coal.The area of the low-temperature abnormal precursor is approximately 3%–6%,which is higher than the 1%–2%of the gas-free coal.With increasing gas pressure,the area of the high-temperature anomalous precursor gradually decreases,and the area of the low-temperature anomalous precursor gradually increases.The highand low-temperature anomalous precursors of gas-bearing coal are mainly caused by gas desorption,volume expansion,and thermal friction.The presence of gas inhibits the increase in IRT on the coal surface and increases the difficulty of infrared radiation(IR)monitoring and early warning for gas-bearing coal.

Device topological thermal management of β-Ga_(2)O_(3) Schottky barrier diodes

The ultra-wide bandgap semiconductor β gallium oxide(β-Ga_(2) O_(3)) gives promise to low conduction loss and high power for electronic devices. However, due to the natural poor thermal conductivity of β-Ga_(2) O_(3), their power devices suffer from serious self-heating effect. To overcome this problem, we emphasize on the effect of device structure on peak temperature in β-Ga_(2) O_(3) Schottky barrier diodes(SBDs) using TCAD simulation and experiment. The SBD topologies including crystal orientation of β-Ga_(2) O_(3), work function of Schottky metal, anode area, and thickness, were simulated in TCAD, showing that the thickness of β-Ga_(2) O_(3) plays a key role in reducing the peak temperature of diodes. Hence, we fabricated β-Ga_(2) O_(3) SBDs with three different thickness epitaxial layers and five different thickness substrates. The surface temperature of the diodes was measured using an infrared thermal imaging camera. The experimental results are consistent with the simulation results. Thus, our results provide a new thermal management strategy for high power β-Ga_(2) O_(3) diode.

Geochemical Indications of Possible Gas Hydrates in the Northeastern South China Sea

Gas hydrate, mainly composed of hydrocarbon gas and water, is considered to be a clean energy in the 21st century. Many indicators such as BSRs （Bottom-Simulating Reflections）, which are thought to be related to gas hydrate, are found in the South China Sea （SCS） in recent years. The northeastern part of the SCS is taken as one of the most potentials in the area by many scientists. It is situated in the conjunction of the northern divergent continental margin and the eastern convergent island margin, whose geological settings are much preferable for gas hydrate to occur. Through this study, brightness temperature anomalies recorded by satellite-based thermal infrared remotely sensed images before or within the imminent earthquake, the high content of hydrocarbon gas acid-degassed from subsurface sediment and the high radioactive thermoluminescence value of subsurface sediment were found in the region. Sometimes brightness temperature anomalies alone exist in the surrounding of the Dongsha Islands. The highest content of hydrocarbon gas amounts to 393 μL methane per kilogram sediment and the highest radioactive thermoluminescence value is 31752 unit; their geometric averages are 60.5 μL/kg and 2688.9 unit respectively. What is more inspiring is that there are three sites where the methane contents are up to 243, 268 and 359μL/kg and their radioactive thermoluminescence values are 8430, 9537 and 20826 unit respectively. These three locations are just in the vicinity of one of the highest confident BSRs identified by predecessors. Meanwhile, the anomalies are generally coincident with other results such as headspace gas anomaly in the sediment and chloride anomaly in the interstitial water in the site 1146 of Leg 184. The above-mentioned anomalies are most possibly to indicate the occurrence of gas hydrate in the northeastern SCS.

Progress on CASEarth Satellite Development

CASEarth satellite is the first space Earth science satellite produced by the Chinese Academy of Sciences.The satellite has three payloads:high-definition Thermal Infrared Spectrometer(TIS),highdefinition Glimmer Imager for Urbanization(GIU),and high-definition Multispectral Imager for Inshore(MII).These payloads are used to explore the urbanization level and residential layout,the coastal ecosystem,and new methods and approaches of environmental detection during night-time and even under conditions of polar aurora and provide scientific evidence for the refined depiction of human traces.The CASEarth satellite can provide space observation data for A Project on Big Earth Data Science Engineering as well as scientific and application studies inside and outside China.

Atmospheric correction of Landsat data for the retrieval of sea surface temperature in coastal waters

A mono-window algorithm was introduced to retrieve sea surface temperature （SST） using Landsat data in coastal waters. In this algorithm, the effective mean air temperature and the water vapor content of air column were estimated with the local meteorological parameters of air temperature and relative humidity, based on the facts that in the troposphere, （ 1 ） air temperature decreases linearly with the altitude, and （2） water vapor content lapses exponentially with the altitude. The sea-truth temperature data and MODIS Terra SST product were used to validate the SST retrieved from Landsat TM and ETM ＋ thermal infrared （TIR） data with the algorithm. The results show that the algorithm can improve the spatial temperature contrast which is often masked due to water vapor effects, and the temperature derived from the algorithm is closer to the sea-truth SST. When applying the algorithm, the initial parameters of air temperature and relative humidity can be easily collected from local meteorological stations, and there is no need to identify the model of air profile.

The extraction of elevation information of ice-sheet surface on south area of the Larsemann Hills in East Antarctica

Based on the setting up of the function relation between the radiant brightness of ice surface and the elevation control point in Antarctica, the experiments for the extraction of elevation information by using thermal infrared image of Landsat TM band 6, and the ice surface topographical maps in area nearby Larsemann Hills have been performed.

Basic Study of Air Leakage Position Based on Thermography Mosaic Technology

When locating the leakage of thermal field of a certain container, it is hard for us to evaluate the leakage with one or several separate thermal infrared images. Instead, panoramic imagery with a wide visual angle and high distinguishability is always needed. However, we can only get images for part of the scene because of the limited visual field of thermography and the large size of the measured object in practical. What is more, the hardware that can be used to get panoramic images is always expensive and cannot be used in large scale. Therefore, this paper introduces image mosaic technology, which can be used to get the intact thermal infrared image of the measured and increase the efficiency of detection. The experiment results demonstrate its effectiveness.