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.

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.

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.

Resistivity and thermal infrared precursors associated with cemented backfill mass

The stability of cemented backfill mass is important to keep miners and equipment safe in underground backfill miming.The stress-strain behavior, resistivity and thermal infrared(TIR) characteristics of backfill mass under uniaxial compression were investigated. The monitoring system consisted of a TIR observation system, a stress-strain monitoring system and a resistivity measurement system. Precursory information for impending failure of cemented backfill mass was collected, including TIR, strain and resistivity precursors. The sensitivity and difference of different monitoring information to the same failure event were compared.The results show that the time-space evolution process of the resistivity and TIR is basically the same as the whole process from compression deformation to failure of backfill mass, and the time variation of resistivity and TIR is obviously characterized by stage.The resistivity precursor turns out earlier than the TIR and the strain. The resistivity relation with loading compression is anti-symmetry, decreasing as the compression stress increases before the peak strength of backfill mass. However, when the backfill mass enters into the phase of failure, the resistivity starts to increase as the stress increases. The change of the resistivity growth direction can be regarded as the resistivity-caution-point for the failure of backfill mass under uniaxial compression. It is also indicated that the TIR information mainly represents the surface temperature evolution in the process of compression before the backfill enters into the plastic-yield state. It can be a valuable tool to obtain the precursors for failure of cemented backfill mass for backfill mines.

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.

Developing selective mining capability for longwall shearers using thermal infrared-based seam tracking

Longwall mining continues to remain the most efficient method for underground coal recovery. A key aspect in achieving safe and productive longwall mining is to ensure that the shearer is always correctly positioned within the coal seam. At present, this machine positioning task is the role of longwall personnel who must simultaneously monitor the longwall coal face and the shearer's cutting drum position to infer the geological trends of the coal seam. This is a labour intensive task which has negative impacts on the consistency and quality of coal production. As a solution to this problem, this paper presents a sensing method to automatically track geological coal seam features on the longwall face, known as marker bands, using thermal infrared imaging. These non-visible marker bands are geological features that link strongly to the horizontal trends present in layered coal seams. Tracking these line-like features allows the generation of a vertical datum that can be used to maintain the shearer in a position for optimal coal extraction. Details on the theory of thermal infrared imaging are given, as well as practical aspects associated with machine-based implementation underground. The feature detection and tracking tasks are given with real measurements to demonstrate the efficacy of the approach. The outcome is important as it represents a new selective mining capability to help address a long-standing limitation in longwall mining operations.

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.

INFRARED THERMAL IMAGE STUDY ON THE FOREWARNING OF COAL AND SANDSTONE FAILURE UNDER LOAD

In the experimental study, AGE-782 thermal instrument was used to detect the infrared radiation variation of coal and sandstone (wave-length range 3.6～5.5 μm was used). It's discovered that coal and sandstone failure under load have three kinds of infrared thermal features as well as infrared forewarning messages. That are: (1) temperature rises gradually but drops before failure ; (2) temperature rises gradually but quickly rises before failure; (3) first rises,then drops and lower temperature emerges before failure. The further researches and the prospect of micro-wave remote sensing detection .on ground pressure is also discussed.

Improving wavelet reconstruction algorithm to achieve comprehensive application of thermal infrared remote sensing data from TM and MODIS

According to the data characteristics of Landsat thematic mapper （TM） and MODIS, a new fu sion algorithm about thermal infrared data has been proposed in the article based on improving wave let reconstruction. Under the domain of neighborhood wavelet reconstruction, data of TM and MO DIS are divided into three layers using wavelet decomposition. The texture information of TM data is retained by fusing highfrequency information. The neighborhood correction coefficient method （NC CM） is set up based on the search neighborhood of a certain size to fuse lowfrequency information. Thermal infrared value of MODIS data is reduced to the space value of TM data by applying NCCM. The data with high spectrum, high spatial and high temporal resolution, are obtained through the al gorithm in the paper. Verification results show that the texture information of TM data and high spec tral information of MODIS data could be preserved well by the fusion algorithm. This article could provide technical support for high precision and fast extraction of the surface environment parame ters.

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.

New Progress in the Application of Satellite Thermal Infrared Imagery to Earthquake Prediction

The concept of stochastic resonance (SR) has been introduced into the analysis of satellite thermal infrared images. Six kinds of anomalous phenomena related to crustal movement were recognized in satellite thermal infrared images. Six diagnostic indicators for the prediction of global earthquakes with magnitude ≥6.0 and their quantitative evaluation standards have been established. The microscopic behavior of global crustal movement is successfully controlled by using satellite thermal infrared imagery, and the occurrence time and magnitude of over 80% of global strong earthquakes occurred since the foundation of the observation station have been successfully predicted. It is believed that the combination of satellite thermal infrared information with macroscopic anomalous phenomena will play an important role in earthquake hazard reduction.

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.

Thermal Infrared Salient Human Detection Model Combined with Thermal Features in Airport Terminal

Target detection in low light background is one of the main tasks of night patrol robots for airport terminal.However,if some algorithms can run on a robot platform with limited computing resources,it is difficult for these algorithms to ensure the detection accuracy of human body in the airport terminal. A novel thermal infrared salient human detection model combined with thermal features called TFSHD is proposed. The TFSHD model is still based on U-Net,but the decoder module structure and model lightweight have been redesigned. In order to improve the detection accuracy of the algorithm in complex scenes,a fusion module composed of thermal branch and saliency branch is added to the decoder of the TFSHD model. Furthermore,a predictive loss function that is more sensitive to high temperature regions of the image is designed. Additionally,for the sake of reducing the computing resource requirements of the algorithm,a model lightweight scheme that includes simplifying the encoder network structure and controlling the number of decoder channels is adopted. The experimental results on four data sets show that the proposed method can not only ensure high detection accuracy and robustness of the algorithm,but also meet the needs of real-time detection of patrol robots with detection speed above 40 f/s.

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.

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.

9μm Cutoff 128×128 AlGaAs/GaAs Quantum Well Infrared Photodetector Focal Plane Arrays

We design and fabricate a 128 × 128 AlGaAs/GaAs quantum well infrared photodetector focal plane array （FPA）. The device is achieved by metal organic chemical vapor deposition and GaAs integrated circuit processing technology. A test structure of the photodetector with a mesa size of 300μm × 300μm is also made in order to obtain the device parameters. The measured dark current density at 77K is 1.5 × 10^-3A/cm^2 with a bias voltage of 2V. The peak of the responsivity spectrum is at 8.4μm,with a cutoff wavelength of 9μm. The blackbody detectivity is shown to be 3.95 × 10^8 （cm · Hz^1/2）/W. The final FPA is flip-chip bonded on a CMOS read-out integrated circuit. The infrared thermal images of some targets at room temperature background are successfully demonstrated at 80K operating temperature with a ratio of dead pixels of less than 1%.

Research Progress on Economic Forest Water Stress Based on Bibliometrics and Knowledge Graph

This study employed the bibliometric software CiteSpace 6.1.R6 to analyze the correlation between thermal infrared,spectral remote sensing technology,and the estimation of economic forest water stress.It aimed to review the development and current status of this field,as well as to identify future research trends.A search was conducted on the China National Knowledge Infrastructure(CNKI)database using the keyword“water stress”for relevant studies from 2003 to 2023.The visual analysis function of CNKI was used to generate the distribution of annual publication volume,and CiteSpace 6.1.R6 was utilized to create network maps illustrating collaboration among authors and institutions.The study also analyzed the hotspots and frontiers of economic forest water stress.As a result,a total of 6664 academic journal articles related to water stress were retrieved.Considerable collaboration networks were observed among scholars and institutions,with a focus on using crown temperature monitoring to diagnose crop water stress.Based on the research findings,it was evident that the primary research trend involved the use of thermal infrared and spectral remote sensing technology for estimating water stress,making it a future research hotspot.

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.