Simulations of Aerosol Optical Properties to Top of Atmospheric Reflected Sunlight in the Near Infrared CO_2 Weak Absorption Band

Over the Asian continent,high aerosol loading is critical to ensure the high accuracy of CO_2 retrieval in the near infrared absorption band.Simulations were performed to explore the effect of light path modification by aerosol son the atmospheric CO_2 near infrared band(6140-6270 cm^(-1)).The Vector LInearized Discrete Ordinate Radiative Transfer(VLIDORT) model and the Line-By-Line Radiative Transfer Model(LBLRTM) were used for forward calculations.The U.S.standard atmosphere was used for atmospheric profiles.The results indicate that the aerosols caused similar effects to increases in CO_2 in the planetary boundary layer and became more significant with aerosol layer rising while aerosol optical depth was 0.1.This effect will cause an over estimation of the CO_2 mixing ratio in the retrieval process and an under estimation in the aerosol layer.The results also indicate that the effect of urban and industrial aerosols is smaller than that of non-absorbing and dust aerosols because of the nearly constant absorption properties in the near infrared band.

Sunglint Impact on Atmospheric Soundings from Hyperspectral Resolution Infrared Radiances

The mid-wave infrared band （3-5 #rn） has been widely used for atmospheric soundings. The sunglint impact on the atmospheric parameter retrieval using this band has been neglected because the reflected radiances in this band are significantly less than those in the visible band. In this study, an investigation of sunglint impact on the atmospheric soundings was conducted with Atmospheric InfraRed Sounder ob- servation data from 1 July to 7 July 2007 over the Atlantic Ocean. The impact of sunglint can lead to a brightness temperature increase of 1.0 K for the surface sensitive sounding channels near 4.58 #m. This contamination can indirectly cause a positive bias of 4 g kg-1 in the water vapor retrieval near the ocean surface, and it can be corrected by simply excluding those contaminated channels.

Rapid identification and preliminary evaluation of quality characters of oilseed sunflower by near infrared spectroscopy

To clarify the quality characters,understand the genetic diversity and screen elite lines among different oilseed sunflowers,the contents of crude fat,oleic acid,linoleic acid,palmitic acid and stearic acid of 525 oil sunflowers(including 375 germplasm accessions and 150 inbred lines)were detected by near-infrared spectroscopy(NIRS);the genetic variation and correlation analysis of quality traits were also performed.The results showed that oleic acid and linoleic acid had rich diversities with large variation ranges for each material type.Similar to the relation between crude fat content and palmitic acid content,significantly negative relation with high estimated value existed between oleic acid and linoleic acid content,while stearic acid content positively associated with oleic acid and palmitic acid content.Principal component analysis indicated that 5 quality traits were integrated into 2principal component factors(linoleic acid negative factor and palmitic acid factor)with the contribution rate of 88.191%,which could be used for evaluating sunflower quality.525 oilseed sunflowers were clustered into 3groups with obvious differences of quality characters,materials in Group I had high contents of oleic acid and low crude fat,but the opposite was found in GroupⅢ.59 superior quality accessions were obtained using large-scale and rapid near-infrared spectroscopy,and these excellent materials were verified by the traditional national chemical standard method.This research provided materials and significant reference for sunflower genetic research and quality breeding.

Lightweight Dual‑Functional Segregated Nanocomposite Foams for Integrated Infrared Stealth and Absorption‑Dominant Electromagnetic Interference Shielding

Lightweight infrared stealth and absorption-dominant electromagnetic interference(EMI)shielding materials are highly desirable in areas of aerospace,weapons,military and wearable electronics.Herein,lightweight and high-efficiency dual-functional segregated nanocomposite foams with microcellular structures are developed for integrated infrared stealth and absorption-dominant EMI shielding via the efficient and scalable supercritical CO_(2)(SC-CO_(2))foaming combined with hydrogen bonding assembly and compression molding strategy.The obtained lightweight segregated nanocomposite foams exhibit superior infrared stealth performances benefitting from the synergistic effect of highly effective thermal insulation and low infrared emissivity,and outstanding absorption-dominant EMI shielding performances attributed to the synchronous construction of microcellular structures and segregated structures.Particularly,the segregated nanocomposite foams present a large radiation temperature reduction of 70.2℃ at the object temperature of 100℃,and a significantly improved EM wave absorptivity/reflectivity(A/R)ratio of 2.15 at an ultralow Ti_(3)C_(2)T_(x) content of 1.7 vol%.Moreover,the segregated nanocomposite foams exhibit outstanding working reliability and stability upon dynamic compression cycles.The results demonstrate that the lightweight and high-efficiency dual-functional segregated nanocomposite foams have excellent potentials for infrared stealth and absorption-dominant EMI shielding applications in aerospace,weapons,military and wearable electronics.

Development of a Qualitative near Infrared Screening Method for Quality Consistency Assessment of Virgin Sunflower Oil

Near infrared spectroscopy offers advantages in the analysis of vegetable oils such as rapidity, relative cost-effectiveness, and usually no need for sample preparation. Virgin Sunflower oils were used as reference standards to develop spectra library for qualitative identification and validation of the method. This model was validated by correct classification method using positive and negative control samples. Various market samples of virgin sunflower oil were purchased and compared with spectra library. The results of spectral analysis of reference library and market samples were correlated using Mahalanobis distance method. Analysis involved 22 market samples. When these samples were matched against calibration samples, 4 samples out of 22 which are about 18.2% were not matched by the reference model. These market samples had Mahalanobis distance values between 4.2 and 6.7, which are greater than maximum permissible value of 3. Some of adulterants mentioned were Korie oil and pumpkin seeds oil.

Fusion SST from Infrared and Microwave Measurement of FY-3D Meteorological Satellite

Sea surface temperature(SST)is one of the important parameters of global ocean and climate research,which can be retrieved by satellite infrared and passive microwave remote sensing instruments.While satellite infrared SST offers high spatial resolution,it is limited by cloud cover.On the other hand,passive microwave SST provides all-weather observation but suffers from poor spatial resolution and susceptibility to environmental factors such as rainfall,coastal effects,and high wind speeds.To achieve high-precision,comprehensive,and high-resolution SST data,it is essential to fuse infrared and microwave SST measurements.In this study,data from the Fengyun-3D(FY-3D)medium resolution spectral imager II(MERSI-II)SST and microwave imager(MWRI)SST were fused.Firstly,the accuracy of both MERSIII SST and MWRI SST was verified,and the latter was bilinearly interpolated to match the 5km resolution grid of MERSI SST.After pretreatment and quality control of MERSI SST and MWRI SST,a Piece-Wise Regression method was employed to correct biases in MWRI SST.Subsequently,SST data were selected based on spatial resolution and accuracy within a 3-day window of the analysis date.Finally,an optimal interpolation method was applied to fuse the FY-3D MERSI-II SST and MWRI SST.The results demonstrated a significant improvement in spatial coverage compared to MERSI-II SST and MWRI SST.Furthermore,the fusion SST retained true spatial distribution details and exhibited an accuracy of–0.12±0.74℃compared to OSTIA SST.This study has improved the accuracy of FY satellite fusion SST products in China.

Infrared and Visible Image Fusion Based on Res2Net-Transformer Automatic Encoding and Decoding

A novel image fusion network framework with an autonomous encoder and decoder is suggested to increase thevisual impression of fused images by improving the quality of infrared and visible light picture fusion. The networkcomprises an encoder module, fusion layer, decoder module, and edge improvementmodule. The encoder moduleutilizes an enhanced Inception module for shallow feature extraction, then combines Res2Net and Transformerto achieve deep-level co-extraction of local and global features from the original picture. An edge enhancementmodule (EEM) is created to extract significant edge features. A modal maximum difference fusion strategy isintroduced to enhance the adaptive representation of information in various regions of the source image, therebyenhancing the contrast of the fused image. The encoder and the EEM module extract features, which are thencombined in the fusion layer to create a fused picture using the decoder. Three datasets were chosen to test thealgorithmproposed in this paper. The results of the experiments demonstrate that the network effectively preservesbackground and detail information in both infrared and visible images, yielding superior outcomes in subjectiveand objective evaluations.

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.

CAEFusion: A New Convolutional Autoencoder-Based Infrared and Visible Light Image Fusion Algorithm

To address the issues of incomplete information,blurred details,loss of details,and insufficient contrast in infrared and visible image fusion,an image fusion algorithm based on a convolutional autoencoder is proposed.The region attention module is meant to extract the background feature map based on the distinct properties of the background feature map and the detail feature map.A multi-scale convolution attention module is suggested to enhance the communication of feature information.At the same time,the feature transformation module is introduced to learn more robust feature representations,aiming to preserve the integrity of image information.This study uses three available datasets from TNO,FLIR,and NIR to perform thorough quantitative and qualitative trials with five additional algorithms.The methods are assessed based on four indicators:information entropy(EN),standard deviation(SD),spatial frequency(SF),and average gradient(AG).Object detection experiments were done on the M3FD dataset to further verify the algorithm’s performance in comparison with five other algorithms.The algorithm’s accuracy was evaluated using the mean average precision at a threshold of 0.5(mAP@0.5)index.Comprehensive experimental findings show that CAEFusion performs well in subjective visual and objective evaluation criteria and has promising potential in downstream object detection tasks.

Failure mechanism and infrared radiation characteristic of hard siltstone induced by stratification effect

The deformation in sedimentary rock induced by train loads has potential threat to the safe operation of tunnels. This study investigated the influence of stratification structure on the infrared radiation and temporal damage mechanism of hard siltstone. The uniaxial compression tests, coupled with acoustic emission(AE) and infrared radiation temperature(IRT) were conducted on siltstones with different stratification effects. The results revealed that the stratigraphic structure significantly affects the stress-strain response and strength degradation characteristics. The mechanical parameters exhibit anisotropy characteristics, and the stratification effect exhibits a negative correlation with the cracking stress and peak stress. The failure modes caused by the stratification effect show remarkable anisotropic features, including splitting failure(Ⅰ: 0°-22.50°, Ⅱ: 90°), composite failure(45°), and shearing failure(67.50°). The AE temporal sequences demonstrate a stepwise response characteristic to the loading stress level. The AE intensity indicates that the stress sensitivity of shearing failure and composite failure is generally greater than that of splitting failure. The IRT field has spatiotemporal migration and progressive dissimilation with stress loading and its dissimilation degree increases under higher stress levels. The stronger the stratification effect, the greater the dissimilation degree of the IRT field. The abnormal characteristic points of average infrared radiation temperature(AIRT) variance at local stress drop and peak stress can be used as early and late precursors to identify fracture instability. Theoretical analysis shows that the competitive relationship between compaction strengthening and fracturing damage intensifies the dissimilation of the infrared thermal field for an increasing stress level. The present study provides a theoretical reference for disaster warnings in hard sedimentary rock mass.

Django框架下的Sun求职平台构建与功能实现

本文基于Django框架,设计与实现了Sun求职平台,旨在为求职者和招聘方提供一个高效、便捷的互联网招聘平台。通过采用Django的模型-视图-控制器(Model-View-Controller)架构,实现了用户注册、登录、简历上传、职位发布等核心功能。在前端方面,采用了Bootstrap框架进行页面布局,使界面简洁美观且具有响应性。在后端方面,利用Django的ORM系统实现了数据库的管理和交互,确保了系统的稳定性和安全性。通过整合第三方认证系统,提高了用户体验的同时,保障了信息的真实性。最终,Sun求职平台通过完善的功能和友好的界面,为求职者和企业搭建了一个高效的沟通桥梁,促进了人才与岗位的精准匹配。

Upconversion of Infrared Photons Enables Rapid Organic Synthesis under Sunlight

A research group led by Prof.WU Kaifeng from the Dalian Institute of Chemical Physics(DICP)of the Chinese Academy of Sciences(CAS)has reported the efficient near-infrared photon upconversion sensitized by leadfree semiconductor nanocrystals and demonstrated its novel application in solar synthesis.

Sunspot Group Detection and Classification by Dual Stream Convolutional Neural Network Method

The automatic detection and analysis of sunspots play a crucial role in understanding solar dynamics and predicting space weather events.This paper proposes a novel method for sunspot group detection and classification called the dual stream Convolutional Neural Network with Attention Mechanism(DSCNN-AM).The network consists of two parallel streams each processing different input data allowing for joint processing of spatial and temporal information while classifying sunspots.It takes in the white light images as well as the corresponding magnetic images that reveal both the optical and magnetic features of sunspots.The extracted features are then fused and processed by fully connected layers to perform detection and classification.The attention mechanism is further integrated to address the“edge dimming”problem which improves the model’s ability to handle sunspots near the edge of the solar disk.The network is trained and tested on the SOLAR-STORM1 data set.The results demonstrate that the DSCNN-AM achieves superior performance compared to existing methods,with a total accuracy exceeding 90%.

Infrared microspectroscopy beamline BL06B at SSRF

The infrared microspectroscopy beamline(BL06B) is a phase Ⅱ beamline project at the Shanghai Synchrotron Radiation Facility(SSRF). The construction and optical alignment of BL06B were completed by the end of 2020. By 2021, it became accessible to users. The synchrotron radiation infrared(SRIR) source included edge radiation(ER) and bending magnet radiation(BMR). The extracted angles in the horizontal and vertical directions were 40 and 20 mrad, respectively. The photon flux, spectral resolution, and focused spot size were measured at the BL06B endstation, and the experimental results were consistent with theoretical calculations. SRIR light has a small divergence angle, high brightness, and a wide wavelength range. As a source of IR microscopy, it can easily focus on a diffraction-limited spatial resolution with a high signal-to-noise ratio(SNR). The BL06B endstation can be applied in a wide range of research fields, including materials, chemistry, biology, geophysics, and pharmacology.

ESIT 2024: Gathering of Global Minds to Hangzhou for Cutting-Edge Infrared and Terahertz Innovation

The third Earth&Space:from Infrared to Terahertz International Conference(ESIT 2024)successfully took place in Hangzhou,China,from September 20 to 22,2024.Co-hosted by the Shanghai Institute of Technical Physics,Chinese'Academy of Sciences(SITP)along with five prestigious institutions,the conference provided a premier platform for international collaboration on cutting-edge developments in infrared,terahertz,and space exploration technologies.

Erratum to:Deriving Temporal and Vertical Distributions of Methane in Xianghe Using Ground-based Fourier Transform Infrared and Gas-analyzer

“Diurnal variation of CH4 at the surface from spring to winter.The time units are in local time(+8 h UTC).The error bar is 1σfor all the observed hourly mean data within that season at that local time.”in the caption of Fig.8 on Page 604 should be“Diurnal variation of CH4 at the surface from spring to winter.The time units are in UTC.The error bar is 1σfor all the observed hourly mean data within that season at that local time.”

Multifunctional MXene/Carbon Nanotube Janus Film for Electromagnetic Shielding and Infrared Shielding/Detection in Harsh Environments

Multifunctional,flexible,and robust thin films capable of operating in demanding harsh temperature environments are crucial for various cutting-edge applications.This study presents a multifunctional Janus film integrating highly-crystalline Ti_(3)C_(2)T_(x) MXene and mechanically-robust carbon nanotube(CNT)film through strong hydrogen bonding.The hybrid film not only exhibits high electrical conductivity(4250 S cm^(-1)),but also demonstrates robust mechanical strength and durability in both extremely low and high temperature environments,showing exceptional resistance to thermal shock.This hybrid Janus film of 15μm thickness reveals remarkable multifunctionality,including efficient electromagnetic shielding effectiveness of 72 dB in X band frequency range,excellent infrared(IR)shielding capability with an average emissivity of 0.09(a minimal value of 0.02),superior thermal camouflage performance over a wide temperature range(−1 to 300℃)achieving a notable reduction in the radiated temperature by 243℃ against a background temperature of 300℃,and outstanding IR detection capability characterized by a 44%increase in resistance when exposed to 250 W IR radiation.This multifunctional MXene/CNT Janus film offers a feasible solution for electromagnetic shielding and IR shielding/detection under challenging conditions.

The Influence of the Sun and Moon on the Observation of Very High Energy Gamma-ray Sources Using EAS Arrays

With great advance of ground-based extensive air shower arrays,such as LHAASO and HAWC,many very high energy(VHE)gamma-ray sources have been discovered and are being monitored regardless of the day and the night.Hence,the Sun and Moon would have some impacts on the observation of gamma-ray sources,which have not been taken into account in previous analysis.In this paper,the influence of the Sun and Moon on the observation of very high energy gamma-ray sources when they are near the line of sight of the Sun or Moon is estimated.The tracks of all the known VHE sources are scanned and several VHE sources are found to be very close to the line of sight of the Sun or Moon during some period.The absorption of very high energy gamma rays by sunlight is estimated with detailed method and some useful conclusions are achieved.The main influence is the block of the Sun and Moon on gamma rays and the shadow on the cosmic ray background.The influence is investigated considering the detector angular resolution and some strategies on data analysis are proposed to avoid the underestimation of the gamma-ray emission.

Intense Mid-Infrared Laser Pulse Generated via Flying-Mirror Red-Shifting in Near-Critical-Density Plasmas

Relativistic femtosecond mid-infrared pulses can be generated efficiently by laser interaction with near-criticaldensity plasmas.It is found theoretically and numerically that the radiation pressure of a circularly polarized laser pulse first compresses the plasma electrons to form a dense flying mirror with a relativistic high speed.The pulse reflected by the mirror is red-shifted to the mid-infrared range.Full three-dimensional simulations demonstrate that the central wavelength of the mid-infrared pulse is tunable from 3µm to 14µm,and the laser energy conversion efficiency can reach as high as 13%.With a 0.5–10 PW incident laser pulse,the generated mid-infrared pulse reaches a peak power of 10–180 TW,which is interesting for various applications in ultrafast and high-field sciences.

Rice Variety Classification Based on Optimized Near-Infrared Spectral Classification Model

Accurate classification of rice variety is essential to ensure the brand value of high-quality rice products.Considering the impact of sample state on modeling optimization algorithms,rice samples after grinding and sealing were selected.To enhance the accuracy of rice variety classification,we introduced a spectral characteristic wavelength selection method based on adaptive sliding window permutation entropy(ASW-PE).