Similar Wavelengths Research Articles

A machine learning approach to estimate mid-infrared fluxes from WISE data

While the Wide-field Infrared Survey Explorer (WISE) is the largest, best quality infrared all-sky survey to date, a smaller coverage mission Spitzer was designed to have better sensitivity and spatial resolution at similar wavelengths. Confusion and contamination in WISE data result in discrepancies between them. We aim to present a novel approach to work with WISE measurements with the goal of maintaining both its high coverage and vast amount of data while, at the same time, taking full advantage of the higher sensitivity and spatial resolution of Spitzer We have applied machine learning (ML) techniques to a complete WISE data sample of open cluster members, using a training set of paired data from high-quality Spitzer Enhanced Imaging Products (SEIP), MIPS and IRAC, and allWISE catalogs, W1 (3.4 mu m) to W4 (22 mu m) bands. We have tested several ML regression models with the aim of predicting mid-infrared fluxes at MIPS1 (24 mu m) and IRAC4 (8 mu m) bands from WISE variables (fluxes and quality flags). In addition, to improve the prediction quality, we have implemented feature selection techniques to remove irrelevant WISE variables. We have notably enhanced WISE detection capabilities, mostly for the targets with the lowest magnitudes, which previously showed the largest discrepancies with Spitzer . In our particular case, extremely randomized trees was found to be the best algorithm to predict mid-infrared fluxes from WISE variables, attaining coefficients of determination $R^2 and $R^2 for 24 mu m (MIPS1) and 8 mu m (IRAC4), respectively. We have tested our results in members of IC 348 and compared their observed fluxes with the predicted ones in their spectral energy distributions. We show discrepancies in the measurements of Spitzer and WISE and demonstrate the good concordance of our predicted mid-infared fluxes with the real ones. Machine learning is a fast and powerful tool that can be used to find hidden relationships between datasets, as the ones we have shown to exist between WISE and Spitzer fluxes. We believe this approach could be employed for other samples from the allWISE catalog with SEIP positional counterparts, and in other astrophysical studies in which analogous discrepancies might arise when using datasets from different instruments.

Performance Comparison of Selected Filters in Fast Denoising of Oil Palm Hyperspectral Data

Usually, hyperspectral data captured from an airborne UAV or satellite contain some noise that can be severe in some channels. Often, channels that are badly affected by the noise are discarded. This is because the corrupted channels cannot be reclaimed by common filtering techniques, making important information in the affected channels different from those of field spectroscopy of similar wavelengths. In this study, a fast-denoising method is implemented on some channels of oil palm hyperspectral data that are badly affected by noise. The amount of noise is unknown, and it varies across the noisy channels from bad to severe. This is different from the data normally used by many studies, which are essentially clean data spiked with mild noise of known variance. The process starts by identifying which noisy channels to filter based on the level of the estimated noise in them. Then, filtering is conducted within each channel and across channels. Once the noise is removed, the improvement in signal-to-noise ratio (SNR) is calculated for each channel. The performance of Kalman, Wiener, Savitzky–Golay, wavelet, and cosine filters is tested in the same framework and the results are compared in terms of execution time, signal-to-noise ratio, and visual quality. The results show that the Kalman filter slightly outperformed the other filters. The proposed scheme was implemented using MATLAB R2023b running on an Intel i7 processor, and the average execution time was less than 1 second for each channel. To the best of our knowledge, this is the first attempt to filter real oil palm hyperspectral data containing speckle noise using a Kalman filter. This technique can be a useful tool to those working in the oil palm industry.

All-Optical Trapping and Programmable Transport of Gold Nanorods with Simultaneous Orientation and Spinning Control.

Gold nanorods (GNRs) are of special interest in nanotechnology and biomedical applications due to their biocompatibility, anisotropic shape, enhanced surface area, and tunable optical properties. The use of GNRs, for example, as sensors and mechanical actuators, relies on the ability to remotely control their orientation as well as their translational and rotational motion, whether individually or in groups. Achieving such particle control by using optical tools is challenging and exceeds the capabilities of conventional laser tweezers. We present a tool that addresses this complex manipulation problem by using a curve-shaped laser trap, enabling the optical capture and programmable transport of single and multiple GNRs along any trajectory. This type of laser trap combines confinement and propulsion optical forces with optical torque to transport the GNRs while simultaneously controlling their rotation (spinning) and orientation. The proposed system facilitates the light-driven control of GNRs and the quantitative characterization of their motion dynamics including transport speed, spinning frequency, orientation, and confinement strength. We experimentally demonstrate that remote control of the GNRs can be achieved both near a substrate surface (2D trapping) and deep within the sample (3D all-optical trapping). The motion dynamics of two sets of off-resonant GNRs, possessing similar aspect ratios but different resonance wavelengths, are analyzed to highlight the role played by their optical and mechanical properties in the optical manipulation process. The experimental results are supported by a theoretical model describing the observed motion dynamics of the GNRs. This optical manipulation tool can significantly facilitate applications of light-driven nanorods.

Substituent effects in 2-hydroxybenzophenone-based ultraviolet absorbers

2-Hydroxybenzophenone is the simplest molecule among benzophenone-based UV absorbers. Changing the position and type of substituents affects the strength of intramolecular hydrogen bonding and thus modulates the UV absorption properties. In this work, 132 2-hydroxybenzophenone-based UV absorbers with different substituent positions and species were designed to investigate the substituent effect in their UV absorption properties. The results show that when the substituent positions are the same, the characteristic peaks of the compounds containing substituents of the same group of atoms or homologous groups correspond to similar wavelengths. When the substituent groups are the same, the wavelength redshift of the characteristic peaks of the UV absorption spectra of the compounds of the NX and NZ classes is more pronounced than that of the remaining species, and the substituent group containing N atoms causes the molecule to have a more pronounced wavelength redshift. The redshift of the characteristic absorption peaks corresponding to the wavelengths decreases with the increase of the energy level difference. Atoms-in-molecules (AIM) analysis showed that the electron-absorbing group in the compound enhances the hydrogen bond strength to a lesser extent than the electron-donating group. Natural Bond Orbital (NBO) analysis further revealed that the type and position of the substituent groups in the molecular structure influenced the strength of the intramolecular hydrogen bonding by affecting the distribution of the charges among individual atoms in the 2-hydroxybenzophenone molecules. This work aims to reveal the effect of substituents on the UV absorption properties of 2-hydroxybenzophenone-based molecules and to provide theoretical guidance for the design of such UV absorber molecules absorbing UV light at specific wavelengths.

Dicyanomethylenated Diaryldihydropentalenediones that Vary Excited State Decay Rates without Changing Emission Wavelengths

Abstract2‐(3,6‐Bis(4‐methoxyphenyl)‐2,2,5,5‐tetramethyl‐4‐oxo‐4,5‐dihydropentalen‐1(2H)‐ylidene)malononitrile (DPM‐An) and 2,2′‐(3,6‐bis(4‐methoxyphenyl)‐2,2,5,5‐tetramethyl‐2,5‐dihydropentalene‐1,4‐diylidene)dimalononitrile (DPD‐An), both bearing the 2,5‐dihydropentalene core and intramolecular electron donor–acceptor moieties, were prepared and subjected to photophysical studies. The absorption spectra of DPM‐An and DPD‐An in CH2Cl2 at room temperature contain maxima at similar wavelengths of 406 and 409 nm, respectively. These substances do not luminesce in CH2Cl2 solution at room temperature, but they do emit light when present in poly(methyl methacrylate) films. Interestingly, DPM‐An and DPD‐An in the film forms display nearly identical emission (EM) spectra with respective maxima at 592 and 594 nm. In contrast, DPD‐An has a longer EM lifetime than does DPM‐An. Therefore, the dihydropentalene derivatives, exemplified by DPM‐An and DPD‐An, may be a family of substances in which excited state decay rate can be varied without changing EM wavelengths.

Qualitative and Quantitative Analysis of Three-Dimensional Fluorescence Spectra by Improved Parallel Factor Analysis with Internal Standard Sample Embedding.

The strategy of parallel factor analysis, combined with the internal standard method, has been increasingly applied to the qualitative and quantitative analysis of three-dimensional fluorescence spectra of unknown mixed fluorophores. Nevertheless, the disparity in the number of fluorophores included in the internal standard sample set and the number included in test samples may impact the qualitative and quantitative outcomes of parallel factor analysis. In this work, we systematically established the framework of the parallel factor analysis with internal standard sample embedding (ISSE-PARAFAC) strategy. We applied this framework to six datasets representing two scenarios and a real dataset and conducted a detailed discussion on the effects of the disparity between the number of fluorophores in the internal standard sample set and the number in the test set on both qualitative and quantitative results. Additionally, we introduced an enhancement to PARAFAC by aggregating fluorophores with similar emission wavelengths, corresponding to the peaks of emission loadings (spectra) obtained from PARAFAC, as a single fluorophore. This aggregation aimed to mitigate the strong correlation between similar fluorophores. The results imply that the presence of irrelevant fluorophores in the internal standard sample set, whether increased or decreased, does not significantly affect the qualitative and quantitative analysis of target fluorophores in the test set. Moreover, we demonstrated that the improved parallel factor analysis with internal standard sample embedding not only fully decomposes the uncorrelated mixed fluorophores for qualitative analysis but also allows the established linear concentration model for fluorescent components to predict the corresponding fluorophore concentration of test samples, enabling quantitative analysis at the ppm level (mg/L).

Comparison of Vinyldimethylaniline and Indolizine Donor Groups on Si‐Substituted Xanthene Core Shortwave Infrared Fluorophores

AbstractSmall organic molecules absorbing and emitting in the shortwave infrared (SWIR, 1000–2000 nm) region are desirable for biological imaging applications due to low auto‐fluorescence, reduce photon scattering, and good tissue penetration depth of photons which allows for in vivo imaging with high resolution and sensitivity. Si‐substituted xanthene‐based fluorophores with indolizine donors have demonstrated some of the longest wavelengths of absorption and emission from organic dyes. This work seeks to compare an indolizine heterocyclic nitrogen with dimethyl aniline nitrogen donors on otherwise identical Si‐substituted xanthene fluorophores via optical spectroscopy, computational chemistry and electrochemistry. Three donors are compared including an indolizine donor, a ubiquitous dimethyl aniline donor, and a vinyl dimethyl aniline group that keeps the number of π‐bonds consistent with indolizine. Significantly higher quantum yields and molar absorptivity are observed in these studies for a dimethylamine‐based donor relative to a simple indolizine donor absorbing and emitting at similar wavelengths (~1312 nm emission). Substantially longer wavelengths are obtainable by appending aniline‐based groups to the indolizine donor (~1700 nm) indicating longer wavelengths can be accessed with indolizine donors while stronger emitters can be accessed with anilines in place of indolizine.

Topologically Protected Parametric Wavelength Conversion in a Valley Hall Insulator

AbstractNonlinear phenomena are investigated in a topological photonic valley Hall insulator (VHI) using a Kagome system designed to have localized topological boundary state (TBS) at telecommunications wavelengths. Valley Hall topologically protected nonlinear phenomena are demonstrated. Similar transmission properties and parametric wavelength conversion of up to −12 dB are experimentally achieved using sub‐milliwatt average powers in a zigzag interface without back‐scattering, compared with a straight interface. Furthermore, a 7 dB slow light enhancement is observed in the conversion efficiency near the red edge in the transmission band of the boundary state, demonstrating how slow light‐induced backscattering may be circumvented by leveraging the topologically protected boundary state. A Kerr‐induced delocalization of the valley Hall topological state (VHTS) is further experimentally observed, which can be harnessed to control the properties of topological edge states.

Galaxy morphology from z ∼ 6 through the lens of JWST

Context. The James Webb Space Telescope’s (JWST’s) unprecedented combination of sensitivity, spatial resolution, and infrared coverage has enabled a new era of galaxy morphology exploration across most of cosmic history. Aims. We analyze the near-infrared (NIR ∼ 0.8 − 1 μm) rest-frame morphologies of galaxies with log M*/M⊙ > 9 in the redshift range of 0 < z < 6, compare with previous HST-based results and release the first JWST-based morphological catalog of ∼20 000 galaxies in the CEERS survey. Methods. We classified the galaxies in our sample into four main broad classes: spheroid, disk+spheroid, disk, and disturbed, based on imaging with four filters: F150W, F200W, F356W, and F444W. We used convolutional neural networks (CNNs) trained on HST/WFC3 labeled images and domain-adapted to JWST/NIRCam. Results. We find that ∼90% and ∼75% of galaxies at z < 3 have the same early and late and regular and irregular classification, respectively, in JWST and HST imaging when considering similar wavelengths. For small (large) and faint objects, JWST-based classifications tend to systematically present less bulge-dominated systems (peculiar galaxies) than HST-based ones, but the impact on the reported evolution of morphological fractions is less than ∼10%. Using JWST-based morphologies at the same rest-frame wavelength (∼0.8 − 1 μm), we confirm an increase in peculiar galaxies and a decrease in bulge-dominated galaxies with redshift, as reported in previous HST-based works, suggesting that the stellar mass distribution, in addition to light distribution, is more disturbed in the early Universe. However, we find that undisturbed disk-like systems already dominate the high-mass end of the late-type galaxy population (log M*/M⊙ > 10.5) at z ∼ 5, and bulge-dominated galaxies also exist at these early epochs, confirming a rich and evolved morphological diversity of galaxies ∼1 Gyr after the Big Bang. Finally, we find that the morphology-quenching relation is already in place for massive galaxies at z > 3, with massive quiescent galaxies (log M*/M⊙ > 10.5) being predominantly bulge-dominated.

A robust feature wavelength extraction strategy for hyperspectral information:Three cases of potato quality evaluation

Because the existing feature wavelength extraction methods for hyperspectral information are only for some specific property of sample, which has some limitations, a feature wavelength extraction strategy with generalization and robustness is proposed. Namely, a part of the same or similar feature wavelengths are extracted by Wilks Λ statistic coupled with principal component analysis from hyperspectral information of different tested samples, and another part are extracted by partial least squares regression coefficient coupled with texture information. And then the two part of feature wavelengths can be integrated together to form the final feature wavelengths that represent the comprehensive properties of these tested samples. Take potato as the research object, and according to this feature wavelength extraction strategy, 8 feature wavelengths applicable to different potato samples were extracted, and three quality analysis cases were successfully implemented: the variety identification model, quality grade detection model and VC content prediction model. The results show that, based on the 8 feature wavelengths extracted by this strategy, the correction rate of the variety identification is 100 %; and the correction rate of the quality grading is above 92 %; and the R2P of the VC content prediction is 0.9715, which shows that the extracted feature wavelengths can effectively represent the different qualities of potato, and has robustness and generalization. This also provides a reference for the study of feature wavelength extraction methods of other agricultural products.

Unveiling Morphine: A Rapid and Selective Fluorescence Sensor for Forensic and Medical Analysis.

Opioid use, particularly morphine, is linked to CNS-related disorders, comorbidities, and premature death. Morphine, a widely abused opioid, poses a significant global health threat and serves as a key metabolite in various opioids. Here, we present a turn-off fluorescent sensor capable of detecting morphine with exceptional sensitivity and speed in various samples. The fluorescent sensor was developed through the dimerization process of 7-methoxy-1-tetralone and subsequent demethylation to produce the final product. Despite morphine possessing inherent fluorophoric properties and emitting light in an approximately similar wavelength as the sensor's fluorescent blue light, the introduction of the target molecule (morphine) in the presence of the sensor caused a reduction in the sensor's fluorescence intensity, which is attributable to the formation of the sensor-morphine complex. By utilizing this fluorescence quenching sensor, the chemo-selective detection of morphine becomes highly feasible, encompassing a linear range from 0.008 to 40 ppm with an impressive limit of detection of 8 ppb. Consequently, this molecular probe demonstrates a successful application in determining trace amounts of morphine within urine, yielding satisfactory analytical results. The study also explores the effect of several variables on the sensor's response and optimizes the detection of morphine in urine using a response surface methodology with a central composite design.

Joint wave-equation inversion of Rayleigh and Love dispersion curves

Wave-equation dispersion (WD) inversion techniques for surface waves have proven to be a robust way to invert the S-wave velocity model. Unlike 1D dispersion curve inversion, WD method obviates the need for a layered model assumption and reduces the susceptibility to cycle-skipping issues in surface wave full-waveform inversion. Previous WD inversion experiments conducted on Rayleigh and Love waves have highlighted that inverting Love waves yields better stability due to their independence from the P-wave velocity model. Nevertheless, Rayleigh waves possess the advantage of greater penetration depth compared with Love waves with similar wavelengths. Therefore, combining the two types of surface waves is a feasible way to improve the accuracy of S velocity tomograms. In light of this, we develop a novel approach: a joint WD inversion encompassing Rayleigh and Love waves. This innovative technique adjusts the weighting of individual WD gradients using the sensitivity factor of an equivalent layered model, offering a significant advancement in subsurface characterization. Synthetic model tests demonstrate that the joint WD inversion method can generate a more accurate S-wave velocity model, particularly in the presence of complex low-velocity layers or high-velocity layers, when compared with individual wave WD inversion techniques. Simultaneously, the results of field tests validate the effectiveness of the proposed joint WD inversion strategy in producing a more dependable S-wave velocity distribution that aligns closely with the actual geologic structure.

Wavelength-tunable quasi-unidirectional spatiotemporal mode-locked solitons in an isolator-free Er-doped fiber laser

In this letter, we have demonstrated the realization of the wavelength-tunable spatiotemporal mode-locked (STML) operation in an Er-doped partial multimode fiber laser without the intracavity isolator. The laser adopts an all-fiber structure and the saturable absorption effect is attributed to nonlinear multimode interference (NL-MMI) from the single mode fiber-graded index multimode fiber-single mode fiber (SMF-GIMF-SMF) design. The STML laser can operate in the quasi-unidirectional regime with an emission strength difference of larger than 30 dB for the two counter-propagating lasers. And the switching between the dominating operating directions in the clockwise (CW) or counter-clockwise (CCW) directions can be easily achieved by adjusting the MM polarization controller (PC). Both STML conventional solitons (CSs) and the STML soliton molecules are obtained with a similar tunable wavelength from ∼1.56 μm to ∼1.58 μm for the opposite operating directions. Furthermore, the spatial dynamics of the STML soliton are also investigated in detail. The experimental results are of great help for us to explore nonlinear spatiotemporal dynamics and provide potential applications in fields of all-optical signal processing, fiber sensing and information coding.

Analysis of the 3.2–3.3 μm Interstellar Absorption Feature on Three Milky Way Sightlines

We report new analyses of spectra of the 3.2–3.3 μm absorption feature observed in the diffuse interstellar medium toward three Milky Way sources: 2MASS J17470898 − 2829561 (2M1747) and the Quintuplet Cluster, both located in the Galactic center, and Cygnus OB2-12. The 3.2–3.3 μm interval coincides with the CH-stretching region for compact polycyclic aromatic hydrocarbons (PAHs). We focus on the 2M1747 spectrum. Its published optical depth spectrum contains residual telluric transmission features, which arise from the 0.06 difference in mean airmasses between the observations of the source and its telluric standard star. We corrected the published spectrum by adding the airmass residual optical depth spectrum. The corrected spectrum is well fit by a superposition of four Gaussians. The absorption spectra of the other two sources were also fit by four Gaussians, with similar central wavelengths, widths, and relative peak opacities. We associate the three longer wavelength Gaussians covering the 3.23–3.31 μm interval with compact PAHs in positive, neutral, and negative charge states. We identify the shortest-wavelength Gaussian, near 3.21 μm, with irregularly shaped PAHs. Constraints imposed by spectral smoothness on the corrected 2M1747 spectrum, augmented by a PAH cluster formation model for post-asymptotic giant branch stars, suggests that >99% of the PAHs in the diffuse interstellar medium reside in small clusters. This study supports the PAH hypothesis, and it suggests that a family of primarily compact PAHs with a C66H20 (circumvalene) parent is consistent with the observed mid-infrared and ultraviolet interstellar absorption spectrum.

Measurement of the degree of deacetylation in chitosan films by FTIR, 1H NMR and UV spectrophotometry

The chitosan films were prepared from shrimp, squid, and crab to corroborate that regardless of the source of the chitosan, it was possible to measure the degree of deacetylation. In this work, the degree of deacetylation of chitosan was evaluated via UV, FTIR and 1H NMR spectrophotometry methodologies. Values in a range of 74 to 99% degree of deacetylation (DD) were obtained and varied depending on the method used and the source of chitosan. The spectrophotometric method is one of the most commonly used for this determination; however, it has the limitation that D-glucosamine and N-acetylglucosamine share similar wavelengths. All three methods were simple and provided rapid analysis; however, NMR, in particular, was expensive due to its equipment specifications. For this reason, its important to select the simplest method than can be routinely used.•The simplest used technique to determine the degree of deacetylation is infrared spectroscopy.•The degree of acetylation of chitosan is related to its physicochemical properties; its determination is an important parameter due to its association with chitosan applications in different industrial areas.•The 1H NMR method is very precise and requires expensive equipment and trained personal. Thus, it cannot be used routinely to determine the degree of deacetylation.

Comparison of Resonance Modes in Two-Dimensional and Three-Dimensional Microsphere Structures

In this article, we have investigated the performance of a resonator in 2D, in an asymmetric form using the physical method and using the Matlab software, we have analyzed it in 3D. According to the simulation results, in asymmetric 2D and 3D structures, whispering gallery modes, or resonances appeared at similar wavelengths for the same radial and polar mode number. Also, the results obtained from the simulations indicated that the resonances of the asymmetric 2D structure would occur at wavelengths close to the wavelengths of 3D structure and the resonance wavelengths for transverse electric (TE) and while transverse magnetic (TM) modes would not change by altering the lateral mode number. Accordingly, 2D structures can be used to obtain resonance wavelengths in microsphere resonators. Achieving results with high accuracy, as well as faster speed offered by smaller meshing volume is one of the advantages of 2D structures in the physical method.

Identification of Different Classes of VOCs Based on Optical Emission Spectra Using a Dielectric Barrier Helium Plasma Coupled with a Mini Spectrometer.

In this study, a micro helium dielectric barrier discharge (μHDBD) plasma device fabricated using 3D printing and molding techniques was coupled with a mini spectrometer to detect and identify different classes of volatile organic compounds (VOCs) using optical emission spectrometry (OES). We tested 11 VOCs belonging to three different classes (straight-chain alkanes, aromatics, and polar organic compounds). Our results clearly demonstrate that the optical emission spectra of different classes of VOCs show clear differences, and therefore, can be used for identification. Additionally, the emission spectra of VOCs with a similar structure (such as n-pentane, n-hexane, n-heptane, n-octane, and n-nonane) have similar optical emission spectrum shape. Acetone and ethanol also have similar emission wavelengths, but they show different line intensities for the same concentrations. We also found that the side-chain group of aromatics will also affect the emission spectra even though they have a similar structure (all have a benzene ring). Moreover, our μHDBD-OES system can also identify multiple compounds in VOC mixtures. Our work also demonstrates the possibility of identifying different classes of VOCs by the OES shape.

Optomechanical ring resonator for efficient microwave-optical frequency conversion

Phonons traveling in solid-state devices are emerging as a universal excitation for coupling different physical systems. Phonons at microwave frequencies have a similar wavelength to optical photons in solids, enabling optomechanical microwave-optical transduction of classical and quantum signals. It becomes conceivable to build optomechanical integrated circuits (OMIC) that guide both photons and phonons and interconnect photonic and phononic devices. Here, we demonstrate an OMIC including an optomechanical ring resonator (OMR), where co-resonant infrared photons and GHz phonons induce significantly enhanced interconversion. The platform is hybrid, using wide bandgap semiconductor gallium phosphide (GaP) for waveguiding and piezoelectric zinc oxide (ZnO) for phonon generation. The OMR features photonic and phononic quality factors of >1 × 105 and 3.2 × 103, respectively. The optomechanical interconversion between photonic modes achieved an internal conversion efficiency {eta }_{i}=(2.1pm 0.1)% and a total device efficiency {eta }_{{tot}}=0.57{times 10}^{-6} at a low acoustic pump power of 1.6 mW. The efficient conversion in OMICs enables microwave-optical transduction for quantum information and microwave photonics applications.

Retrieving Precipitable Water Vapor Over Land From Satellite Passive Microwave Radiometer Measurements Using Automated Machine Learning

AbstractAccurately retrieving precipitable water vapor (PWV) over wide‐area land surface remains challenging. Unlike passive infrared remote sensing, passive microwave (PMW) remote sensing provides almost all‐weather PWV retrievals. This study develops a PMW‐based land PWV retrieval algorithm using automated Machine learning (ML) (AutoML). Data from the Advanced Microwave Scanning Radiometer 2 serve as the main predictor variables and high‐quality Global Positioning System (GPS) PWV data as the target variable. Unprecedentedly large GPS training samples (over 50 million) from more than 12,000 stations worldwide are used to train the AutoML model. New predictors with clear physical mechanisms enable PWV retrieval over almost any land surface type, including snow cover and near open water. Validation shows good agreement between PWV retrievals and ground observations, with a root mean square error of 3.1 mm. This encouraging outcome highlights the potential of the algorithm for application with other PMW radiometers with similar wavelengths.

Recent advancement of RB noise alleviation techniques in different communication networks and its lacunae: a review

Abstract Telecommunication networks are forced to be advanced day by day for high data rate transportation over long-reach to fulfil the ever-increasing demand of the subscribers. Different used schemes, modulation techniques are smart enough to support high data rate transmission over long distance but some impairment like Rayleigh backscattering (RB) brings a limitation on data rate or transmission distance. RB noise effect arises and affects the system performance when more than one signal of similar wavelengths are transmitted through a same feeder fiber in full-duplex networks and different researchers have already proposed various schemes to eliminate RB noise effect in different transport networks. The present paper surveys and analyses the techniques which proposed in last 15 years for mitigation of RB noise in communication systems. The origin of RB and the impact of it in different communication systems are also explained. All the proposed networks are aimed to support next generation communication systems by providing high data rate (up to 160 Gbps downstream and 20 Gbps upstream) over long reach (up to 115 km single mode fiber link) with lesser RB noise effect but exact quantification of RB noise mitigation is not reported till now which could be a future scope for the new researchers.