Spatial Homogeneity Research Articles

Spatial variation in key functional traits of Mediterranean fucoid algae: Insights from Cystoseira sensu lato intertidal canopies

Cystoseira sensu lato are fucoid algae that form dense stands on intertidal and subtidal rocky reefs sustaining species-rich associated assemblages. The increasing human pressure is causing the decline of these marine forests, raising wide concerns on the ecological consequences of their loss. Yet, little is known about functional trait variables of Cystoseira s.l. species, which are essential to a deeper understanding of their contribution to the functioning of coastal ecosystems. We analysed the intraspecific spatial variation of the total organic matter, Corg, N and P contents in Ericaria amentacea from intertidal rocky shores in the W Mediterranean Sea. Specifically, we quantified spatial patterns of variation of traits at large (100s km), small (1000s m), and local (100s cm) scale. We also explored potential interspecific variation by comparing the combined functional profile of trait variables between E. amentacea and Cystoseira compressa, an often co-occurring or vicariant species. Tissue contents of organic matter, Corg, N and P, were consistent among E. amentacea stands, supporting the hypothesis of a large-scale (100s km) spatial homogeneity of such key traits in this species. Overlapping functional profiles between E. amentacea and C. compressa also suggested putative interspecific trait congruencies. However, a small-scale (1000s m) significant variability was found for all trait variables in E. amentacea. Variance components at small (1000s m) and local (100s cm) scale accounted for the largest contribution to the total spatial variation for all traits, recommending caution in the use of small and local-scale trait values to generalize functional performances of Cystoseira s.l. forests over large areas. This study represents one of the first attempts to shed light on the variability of key functional attributes of Cystoseira s.l. species at a range of spatial scales, which could assist more reliable assessments of their functional role and improve their management and conservation.

Investigation of spatio-temporal inertial cavitation activity for optimization of needle-free ultrasound-enhanced vaccine delivery

Ultrasound-induced cavitation is a promising mechanism for pain-free delivery of vaccines without needles. However, the relationships between cavitation energy and the various bioeffects involved in transdermal vaccination, including skin permeabilization, convective drug transport, reversible and irreversible sonoporation, and immune-stimulation, are not well understood. Previous transdermal ultrasound experiments have demonstrated inhomogeneous delivery across the exposed surface, which remains poorly understood. In this work, we first seek to fully characterize and quantify spatio-temporal cavitation activity across the skin surface, to identify a local cavitation dose that is optimal for all four key bioeffects. We have designed a new in vitro experimental setup that exposes several potential skin models to 265 kHz focused ultrasound, a new generation of protein-based cavitation nuclei (pCaNs), and a fluorescently labelled vaccine analogue, while simultaneously imaging cavitation activity parallel to the skin surface by Passive Acoustic Mapping (PAM). Subsequent staining and multi-photon microscopy of the skin models allows a direct comparison between the PAM-derived spatiotemporal inertial cavitation dose and locations where particular bioeffects were maximized. We will discuss the results of this investigation, how they relate to our recent in vivo study, and whether these findings enable enhancements of the spatial homogeneity and reproducibility of needle-free ultrasound vaccination.

A bidirectional hitting probability for the symmetric Hunt processes

We write σA the first hitting time of set A for the Hunt processes. Let B and BR be compact sets, where BR states far away from B. We assume that the Hunt process is irreducible and conservative and satisfies the Feller property. We consider a relation of the hitting probability of B from BR with the hitting probability of BR from B, without the spatial homogeneity. Our claim is that if the Hunt process satisfies the strong Feller property, then limx→∞Px(σB≤t)=0 implies that limR→∞Py(σBR≤t)=0, for y∈B. Additionally, if the Hunt process is m-symmetric, then both statements are equivalent.

Small Island Effects on the Thermal Biology of the Endemic Mediterranean Lizard Podarcis gaigeae.

Ectotherms are vastly affected by climatic conditions as they rely on external sources of heat to regulate their body temperature, and changes in their habitat thermal quality could seriously affect their overall biology. To overcome the problems of a thermally unfavorable habitat, lizards need to either adjust their thermoregulatory behavior or respond to directional selection and shift their preferred body temperatures. To assess the impact of habitat thermal quality on the thermoregulatory profile, we studied multiple islet and 'mainland' populations of the Skyros wall lizard Podarcis gaigeae, an endemic lacertid to Skyros Archipelago, Greece. We evaluated the effectiveness of thermoregulation (E) using the three main thermal parameters: body (Tb), operative (Te), and preferred (Tpref) temperatures. We first hypothesized that the spatial homogeneity, the scarcity of thermal shelters, and the exposure to higher winds on islets would result in more demanding climate conditions. Second, we anticipated that islet lizards would achieve higher E in response to the lower thermal quality therein. As hypothesized, thermal parameters differed between populations but not in the expected manner. Skyros 'mainland' habitats reached higher temperatures, had more intense fluctuations, and were of lower thermal quality. As a result, lizards showed higher accuracy, precision, and effectiveness of thermoregulation. Noteworthy, we found that lizards from different populations have shifted their thermal profile and preferred body temperatures to cope with the particular conditions prevailing in their habitats. The latter supports the labile view on the evolution of thermoregulation.

Application of high-frequency water injection for the performance improvement of waste-heat-recovery boilers

It has been discussed that injecting water into the intake air can increase thermal efficiency and reduce NOx emissions simultaneously in waste-heat-recovery boilers (WHRB). To increase the evaporation rate of the injected water and recover more thermal energy through the heat exchanger, the water injection amount needs to be controlled properly and droplets in the spray need to be distributed homogeneously with the smallest droplets possible. To achieve this, this study introduces a high-frequency injection strategy that can generate strong in-nozzle turbulence, thus promoting spray atomization and supplying continuous water to the heat exchanger. Three different injection frequencies are applied to investigate water spray characteristics. The water spray structure is visualized using the Mie-scattering technique, and the droplet size is measured using the laser diffraction method. In addition, practical boiler tests are performed to confirm the effect of the high-frequency water injection on the boiler performance. The experimental results showed that the mean droplet size decreased, and the spatial and temporal homogeneity of the spray distribution was improved as the injection frequency increased. As a result of the higher water injection frequency, the evaporation rate and thermal efficiency of the boiler increased, and nitrogen oxide (NOx) emissions decreased.

Investigation of Surface Chemistry of Pemwes Iridium Oxide Catalyst Layers as a Function of Ink Aging Time

Proton exchange membrane water electrolyzers (PEMWEs) are an advanced and effective solution to producing hydrogen from water for green hydrogen production. To improve PEMWEs operation, it is necessary to analyze the catalyst layer (CL) to better understand relationships between surface properties and processing, performance, and durability. However, understanding the CL composition, structure, and morphology at all relevant scales is difficult. X-ray photoelectron spectroscopy (XPS) is a surface-sensitive technique that is capable of measuring subtle differences in chemistry of a sample’s surface within top 3-10 nms. However, there are several challenges associated with limited information that has been reported in the literature thus far.This study focuses on investigating the CLs made with IrO2 catalysts using Mayer Bar coating method, one of the scalable fabrication routes. XPS analysis was conducted using a recently developed approach that mitigates issues with degradation of ionomer induced during X-ray exposure. First, XPS was used to probe variations between different areas of the CLs to assess spatial homogeneity to confirm good quality of the coatings. XPS was also employed to investigate CLs made with inks aged for different amount of time (0, 3, and 14 days), noting some differences in the surface chemistry. Results from this study will discuss the effect of ink age on surface composition at the catalyst-ionomer interface, as well as address specific challenges in fitting the O 1s and Ir 4f core level spectra which are inherently challenging to curve fit. This work motivates further studies investigating other aspects related to processing and fabrication as well as investigations of CLs stability.

Summer dynamics of cyanobacteria in an oligo-mesotrophic temperate lake in Northwest Ireland

Despite the potential adverse consequences they can impart on biotopes, cyanobacteria are an understudied component of lake plankton communities in Ireland. This study, in summer 2019, examined cyanobacterial diversity and associated environmental variables in a lake previously impacted by algal blooms, in north-west Ireland. Vertical profiling showed that photosynthetic pigment concentrations were spatially heterogenous for the majority of the survey. However, water column homogeneity was observed towards the end of the survey, coinciding with increases in pigment concentrations. Sunshine hours, nutrient concentrations and wind speed were stable throughout the survey. Spatial homogeneity in pigments was attributed to an increase in minimal temperatures observed in the water column. PCR-DGGE analysis identified patterns in community composition, indicating a rise in cyanobacterial richness concomitant to increase in temperature and photosynthetic pigments. Band sequencing analysis identified phylotypes similar to the toxigenic species Microcystis sp. These were prominent at the end of the survey and coincided with the presence of the mcyE gene and low levels of microcystins, as indicated by real time PCR and ELISA analyses. The summer background presence of toxigenic cyanobacteria with potential bloom-forming capacity highlights the importance of annual lake cyanotoxin monitoring to inform resource management to protect human and animal health.

How Is Spatial Homogeneity in Precipitation Extremes Changing Globally?

AbstractThe effect of climate change on precipitation intensity is well documented. However, findings regarding changes in spatial extent of extreme precipitation events are still ambiguous as previous studies focused on particular regions and time domains. This study addresses this ambiguity by investigating the pattern of changes in the spatial extent of short duration extreme precipitation events globally. A grid‐based indicator termed Spatial‐Homogeneity is proposed and used to assess the changes of spatial extent in Global Precipitation Measurement records. This study shows that (a) rising temperature causes significant shrinking of precipitation extent in tropics, but an expansion of precipitation extent in arid regions, (b) storms with higher precipitation intensity show a faster decrease in spatial extent, and (c) larger spatial extent storms are associated with higher total precipitable water. Results imply that in a warming climate, tropics may experience severe floods as storms may become more intense and spatially concentrated.

An unsupervised dual contrastive learning framework for scatter correction in cone-beam CT image

Purpose:Cone-beam computed tomography (CBCT) is widely utilized in modern radiotherapy; however, CBCT images exhibit increased scatter artifacts compared to planning CT (pCT), compromising image quality and limiting further applications. Scatter correction is thus crucial for improving CBCT image quality. Methods:In this study, we proposed an unsupervised contrastive learning method for CBCT scatter correction. Initially, we transformed low-quality CBCT into high-quality synthetic pCT (spCT) and generated forward projections of CBCT and spCT. By computing the difference between these projections, we obtained a residual image containing image details and scatter artifacts. Image details primarily comprise high-frequency signals, while scatter artifacts consist mainly of low-frequency signals. We extracted the scatter projection signal by applying a low-pass filter to remove image details. The corrected CBCT (cCBCT) projection signal was obtained by subtracting the scatter artifacts projection signal from the original CBCT projection. Finally, we employed the FDK reconstruction algorithm to generate the cCBCT image. Results:To evaluate cCBCT image quality, we aligned the CBCT and pCT of six patients. In comparison to CBCT, cCBCT maintains anatomical consistency and significantly enhances CT number, spatial homogeneity, and artifact suppression. The mean absolute error (MAE) of the test data decreased from 88.0623 ± 26.6700 HU to 17.5086 ± 3.1785 HU. The MAE of fat regions of interest (ROIs) declined from 370.2980 ± 64.9730 HU to 8.5149 ± 1.8265 HU, and the error between their maximum and minimum CT numbers decreased from 572.7528 HU to 132.4648 HU. The MAE of muscle ROIs reduced from 354.7689 ± 25.0139 HU to 16.4475 ± 3.6812 HU. We also compared our proposed method with several conventional unsupervised synthetic image generation techniques, demonstrating superior performance. Conclusions:Our approach effectively enhances CBCT image quality and shows promising potential for future clinical adoption.

Effects of tropical cyclone Amphan on the copepods of the Ganges estuary

ABSTRACT Tropical cyclones are increasingly affecting estuarine communities. The effects of category-5 tropical cyclone Amphan (landfall on 20 May 2020 near the Ganges estuary mouth) on the copepod community of the Ganges estuary were studied. Copepod assemblages were sampled before (February–December 2019), shortly after (31 May–12 June 2020) and post-(September–November 2020) Amphan periods. It was hypothesized that shortly after Amphan a relatively homogeneous community consisting of a few estuarine specialists would succeed but that would soon be replaced by a heterogeneous one; however, those specialists would continue their dominance. Shortly after Amphan species richness declined but the recovery process was completed within months, led by Paracalanus parvus, Bestiolina similis, Acartia spinicauda, Acartiella tortaniformis and Oithona brevicornis. Spatial homogeneity of the community that prevailed in pre- and shortly after Amphan was lost in post-Amphan. The unilateral dominance of B. similis observed in the pre-Amphan period was challenged by P. parvus, A. spinicauda, A. tortaniformis and O. brevicornis after Amphan. Shortly after Amphan A. spinicauda proliferated and co-dominated the estuary with A. tortaniformis but the latter replaced the former within a few months. The copepod community experienced rearrangements in species composition, abundance and dominance hierarchy; therefore, its regular monitoring is recommended.

Experimental Study of a Room-Temperature Shimming Technology Employing Genetic Algorithm for NMR/MRI Superconducting Magnets

We present a recently developed shimming method that uses a system of room-temperature (RT) orthogonal shimming coils to improve the spatial field homogeneity of high-resolution nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) superconducting magnets. Conventional RT shimming methods require recursive routines of field mapping and RT shim coil current adjustments, which lead to a less effective and time-consuming process. In this paper, we introduce a new RT shimming method that utilizes a process of gradual and automatic search to find an optimal operating point with a genetic algorithm (GA), a type of optimization technique. The proposed algorithm is capable of determining the optimal set of currents for a system of shimming coils to create the best spatial field homogeneity by minimizing the NMR spectral linewidth. We used a commercial 600-MHz NMR magnet with a full NMR spectral linewidth at half maximum (FWHM) of 2.2 ppm, as determined by an NMR test sample contained in a cylindrical glass tube with a diameter of 5 mm to demonstrate that the shimming method can improve the FWHM to 0.15 ppm. The results demonstrate the strong potential of the proposed RT shimming methodology for the auto-shimming process of NMR/MRI applications.

SEM-imaging-based mapping of monofractal and multifractal patterns of the Piper krukoffii Yunck leaf surface architecture

We employed Scanning Electron Microscopy (SEM) to investigate the monofractal and multifractal characteristics of the leaf architecture of Amazon Piper krukoffii Yunck plant. By examining morphological features of the leaves using SEM imaging, we observed pentagonal to polygonal epidermal walls with fine tuberculate relief and characteristic cells over both leaf surfaces. Our Minkowski functionals analysis showed that the adaxial surface of the leaf had greater percolative behavior compared to the abaxial surface. Using monofractal analysis, we found that the adaxial side exhibited higher spatial complexity (FD = 1.6), more percolative features (FS = 0.228), and higher spatial homogeneity (β = 0.297). Although both sides of the leaf exhibited highly multifractal behavior, the abaxial surface showed a decrease in the trend of interval between heights (Δf = 0.583). These results demonstrate that the adaxial and abaxial surfaces of Piper krukoffii have a similar multifractality, but the abaxial side has less variability in vertical complexity, consistent with our monofractal analysis. Our findings prove that the spatial complexity of leaves is strongly related to their growth dynamics and can play a crucial role in the overall health, pest control, and evolutionary achievements.

Evaluating the roughness dynamics ofkefir biofilms grown onAmazon cupuaçu juice: a monofractal andmultifractal approach.

We conducted a comprehensive analysis of the surface microtexture of kefir biofilms grown on Theobroma grandiflorum Shum (cupuaçu) juice using atomic force microscopy. Our goal was to investigate the unique monofractal and multifractal spatial patterns of these biofilms to complement the existing limited literature. The biofilms were prepared dispersing four different concentrations of kefir grains in cupuaçu juice. Our morphological analysis showed that the surface of the obtained biofilms is essentially formed by the presence of cupuaçu fibers and microorganisms like lactobacilli and yeast. The topographic height-based parameter analysis reveals that there is a dependence between surface roughness and the concentration of kefir grains used. The strongly anisotropic well-centralized topographical height distribution of the biofilms also exhibited a quasi-symmetrical and platykurtic pattern. The biofilms exhibit comparable levels of spatial complexity, surface percolation and surface homogeneity, which can be attributed to their similar topographic uniformity. This aspect was further supported by the presence of similar multifractality in the biofilms, suggesting that despite their varying topographic roughness, their vertical growth dynamics follow a similar pattern. Our findings demonstrate that the surface roughness of kefir biofilms cultivated on cupuaçu juice is influenced by the concentration of kefir grains in the precursor solution. However, this dependence follows a consistent pattern across different concentrations. Graphical Abstract.

Oriented lateral growth of two-dimensional materials on c-plane sapphire.

Two-dimensional (2D) semiconducting transition metal dichalcogenides (TMDs) represent the ultimate thickness for scaling down channel materials. They provide a tantalizing solution to push the limit of semiconductor technology nodes in the sub-1 nm range. One key challenge with 2D semiconducting TMD channel materials is to achieve large-scale batch growth on insulating substrates of single crystals with spatial homogeneity and compelling electrical properties. Recent studies have claimed the epitaxy growth of wafer-scale, single-crystal 2D TMDs on a c-plane sapphire substrate with deliberately engineered off-cut angles. It has been postulated that exposed step edges break the energy degeneracy of nucleation and thus drive the seamless stitching of mono-oriented flakes. Here we show that a more dominant factor should be considered: in particular, the interaction of 2D TMD grains with the exposed oxygen-aluminium atomic plane establishes an energy-minimized 2D TMD-sapphire configuration. Reconstructing the surfaces of c-plane sapphire substrates to only a single type of atomic plane (plane symmetry) already guarantees the single-crystal epitaxy of monolayer TMDs without the aid of step edges. Electrical results evidence the structural uniformity of the monolayers. Our findings elucidate a long-standing question that curbs the wafer-scale batch epitaxy of 2D TMD single crystals-an important step towards using 2D materials for future electronics. Experiments extended to perovskite materials also support the argument that the interaction with sapphire atomic surfaces is more dominant than step-edge docking.

Critical mass for Keller–Segel systems with supercritical nonlinear sensitivity

This paper is concerned with the following radially symmetric Keller–Segel systems with nonlinear sensitivity [Formula: see text] and [Formula: see text], posed on [Formula: see text] [Formula: see text] and subjected to homogeneous Neumann boundary conditions. It is well-known that [Formula: see text] is the critical exponent of the systems in the sense that all solutions exist globally if [Formula: see text] and there exist finite-time blowup solutions if [Formula: see text]. Here we consider the supercritical case [Formula: see text] and show a critical mass phenomenon. Precisely, we prove that there exists a critical mass [Formula: see text] such that (1) for arbitrary nonincreasing nonnegative initial data [Formula: see text] with [Formula: see text] and [Formula: see text], the corresponding solution blows up in finite time if [Formula: see text], and if [Formula: see text] we can only prove that the solution blows up in finite time or infinite time; (2) for some nonincreasing nonnegative initial data with [Formula: see text], the corresponding solutions are globally bounded. Our results extend that of Winkler’s paper [M. Winkler, How unstable is spatial homogeneity in Keller–Segel systems? A new critical mass phenomenon in two- and higher-dimensional parabolic–elliptic cases, Math. Ann. 373 (2019) 1237–1282], where he proved similar results for the system with [Formula: see text].

Reliability of smart noise pollution map

AbstractThe problem of noise pollution in Baghdad, the capital city of Iraq, is getting worse every day as a result of the increased volume of traffic. This presents a considerable risk, particularly on the main roads that connect densely populated neighborhoods such as the Al-Sadr City district with the central neighborhoods of the capital. In order to inform decision-makers in urban development and environmental policy about the high values of noise pollution that require remediation and regulation, noise maps are produced. However, two fundamental problems are generally faced in creating a more reliable noise map in the shortest possible time: the excessive time requirements for measuring noise and determining the method of map creation. Therefore, the role of geographic information system (GIS) software in producing noise maps is evident due to the difficulty of increasing the spatial density of measurements and integrating them with spatial information. Hence, an appropriate interpolation method is required. In this article, Moran’sIindex was calculated to assess the spatial autocorrelation of measured traffic noise points. A comparison was made between the Smart Map Plugin ordinary kriging (OK) and the inverse distance weighting (IDW) deterministic interpolation method to determine the best method for producing noise maps for the main entrance and exit roads of Al-Sadr City. The noise values were modeled using the best-performing method. Furthermore, the predictive raster data are displayed in the spatial context as a starting point and reference for identifying and understanding the levels of traffic noise in the selected study area. The locations of selected points for measuring traffic noise values were determined in an organized and homogeneous manner, where noise points for the main entrance and exit roads were opposite each other, and the distance between consecutive noise points on each road was 100 m. Traffic noise measurements were carried out at each selected point using the SVAN977 sound and vibration analyzer. At each measurement point, three noise values (LAeq, Max, Min) were obtained during the three peak times, 7–9 AM, 12–2 PM, and 4–6 PM. QGIS software was used to compare the two interpolation methods, with its strength lying in the use of plugins that facilitate spatial analysis, processing tools, and algorithms. The Smart Map Plugin provided facilities to choose the appropriate semi-variogram in the OK interpolation method. The root mean square error was used to compare the two interpolation methods in order to determine the most suitable method for producing traffic noise maps in the study area. The results indicated that the Smart Map Plugin using OK outperformed the IDW method, as spatial distribution pattern and homogeneity affect the accuracy of interpolation. Moreover, based on the analysis of the three noise attributes (LAeq, Max, Min), the performance of the Smart Map Plugin (OK) was found to be better than IDW when the Moran’sIvalue was high.

Design of 3D printed stage for in situ magnetic field application in magnetic force microscopy

We propose a design of 3D printed magnetic stage that allows application of static magnetic fields during magnetic force microscopy measurements. The stage utilizes permanent magnets providing spatial homogeneous magnetic fields. The design, assembly, and installation are described. Numerical calculations of the field distribution are used to optimize the size of magnets and the spatial homogeneity of the field. The stage offers a compact and scalable design, which can be adapted as an accessory onto several commercially available magnetic force microscopy platforms. The stage’s utility for in situ magnetic field application during magnetic force microscopy measurements is demonstrated on a sample of thin ferromagnetic strips.

Regionalization of an agricultural area by means of multivariate data and their relationship with soybean productivity

Regionalization of an agricultural area by dividing it into different clusters is an important strategy in the precision agriculture scope. Multivariate and spatial data are common in the design of these divisions. This paper sought to characterize regional differences in the area under study through different subsets of variables formed by soil physical-chemical variables and vegetative indices, in an agricultural area for four soybean harvest years in the period from 2013/2014 to 2016/2017. To such end, three subsets were generated comprised by these variables, which presented spatial dependence and were grouped according to their characteristics. By means of decision trees, it was identified which of these variables exerted the most influence on subdivision of the area. The multivariate and non-parametric spatial clustering technique was used to generate the clusters. Finally, by means of maps and boxplots, the spatial relationships between these variables and soybean productivity were evaluated. There was variation across the harvest years in relation to the subset of variables that determined the best design of the different clusters. The regional differences determined by the different variables used in the study showed no relationship with soybean productivity, which presented spatial homogeneity in its data for the harvest years evaluated. This approach is recommended when there is high spatial variability of factors that exert impacts on productivity, advising on using both soil physical-chemical variables and the vegetative indices to explain the causes of soybean productivity spatial variability

Optical Second Harmonic Generation on LaAlO3/SrTiO3 Interfaces: A Review.

As we approach the limits of semiconductor technology, the development of new materials and technologies for the new era in electronics is compelling. Among others, perovskite oxide hetero-structures are anticipated to be the best candidates. As in the case of semiconductors, the interface between two given materials can have, and often has, very different properties, compared to the corresponding bulk compounds. Perovskite oxides show spectacular interfacial properties due to the the rearrangement of charges, spins, orbitals and the lattice structure itself, at the interface. Lanthanum aluminate and Strontium titanate hetero-structures (LaAlO3/SrTiO3) can be regarded as a prototype of this wider class of interfaces. Both bulk compounds are plain and (relatively) simple wide-bandgap insulators. Despite this, a conductive two-dimensional electron gas (2DEG) is formed right at the interface when a LaAlO3 thickness of n≥4 unit cells is deposited on a SrTiO3 substrate. The 2DEG is quite thin, being confined in only one or at least very few mono-layers at the interface, on the SrTiO3 side. A very intense and long-lasting study was triggered by this surprising discovery. Many questions regarding the origin and characteristics of the two-dimensional electron gas have been (partially) addressed, others are still open. In particular, this includes the interfacial electronic band structure, the transverse plane spatial homogeneity of the samples and the ultrafast dynamics of the confined carriers. Among a very long list of experimental techniques which have been exploited to study these types of interfaces (ARPES, XPS, AFM, PFM, …and many others), optical Second Harmonic Generation (SHG) was found to be suitable for investigating these types of buried interfaces, thanks to its extreme and selective interface-only sensitivity. The SHG technique has made its contribution to the research in this field in a variety of different and important aspects. In this work we will give a bird's eye view of the currently available research on this topic and try to sketch out its future perspectives.

A Multi-Attention Autoencoder for Hyperspectral Unmixing Based on the Extended Linear Mixing Model

Hyperspectral unmixing, which decomposes mixed pixels into the endmembers and corresponding abundances, is an important image process for the further application of hyperspectral images (HSIs). Lately, the unmixing problem has been solved using deep learning techniques, particularly autoencoders (AEs). However, the majority of them are based on the simple linear mixing model (LMM), which disregards the spectral variability of endmembers in different pixels. In this article, we present a multi-attention AE network (MAAENet) based on the extended LMM to address the issue of the spectral variability problem in real scenes. Moreover, the majority of AE networks ignore the global spatial information in HSIs and operate pixel- or patch-wise. We employ attention mechanisms to design a spatial–spectral attention (SSA) module that can deal with the band redundancy in HSIs and extract global spatial features through spectral correlation. Moreover, noticing that the mixed pixels are always present in the intersection of different materials, a novel sparse constraint based on spatial homogeneity is designed to constrain the abundance and abstract local spatial features. Ablation experiments are conducted to verify the effectiveness of the proposed AE structure, SSA module, and sparse constraint. The proposed method is compared with several state-of-the-art unmixing methods and exhibits competitiveness on both synthetic and real datasets.