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Bragg interferometry (BI) is an imaging technique based on four-dimensional scanning transmission electron microscopy (4D-STEM) wherein the intensities of select overlapping Bragg disks are fit or more qualitatively analyzed in the context of simple trigonometric equations to determine local stacking order. In 4D-STEM based approaches, the collection of full diffraction patterns at each real-space position of the scanning probe allows the use of precise virtual apertures much smaller and more variable in shape than those used in conventional dark field imaging such that even buried interfaces marginally twisted from other layers can be targeted. With a coarse-grained form of dark field ptychography, BI uses simple physically derived fitting functions to extract the average structure within the illumination region and is, therefore, viable over large fields of view. BI has shown a particular advantage for selectively investigating the interlayer stacking and associated moiré reconstruction of bilayer interfaces within complex multi-layered structures. This has enabled investigation of reconstruction and substrate effects in bilayers through encapsulating hexagonal boron nitride and of select bilayer interfaces within trilayer stacks. However, the technique can be improved to provide a greater spatial resolution and probe a wider range of twisted structures, for which current limitations on acquisition parameters can lead to large illumination regions and the computationally involved post-processing can fail. Here, we analyze these limitations and the computational processing in greater depth, presenting a few methods for improvement over previous works, discussing potential areas for further expansion, and illustrating the current capabilities of this approach for extracting moiré-scale strain. [ABSTRACT FROM AUTHOR]

This paper introduces a novel method for the three-dimensional characterization of flyers based on microscopic photonic Doppler velocimetry (PDV) velocity field measurements. By strategically positioning 56 PDV velocity measurement spots within a circle of 0.50 mm diameter at an interval of approximately 58 μm, we achieve spatially resolved measurements of the velocity history of the flyer during its flight within the barrel and subsequent impact on a transparent window. Crucial data, such as displacement history, impact time, and impact pulse duration, can be extracted at each measurement spot. Furthermore, a correlation analysis of these datasets enables the reconstruction of the flyer's three-dimensional morphology, both during its flight inside the barrel and at the critical moment of impact with the window. This method offers a remarkable temporal resolution in the order of nanoseconds and a spatial resolution in the order of micrometers. With the characteristics of high spatial resolution and high experimental efficiency, the microscope PDV technology is poised to become an essential research tool in the study of action mechanisms, design optimization, and determination of initiation criteria for exploding foil initiators. [ABSTRACT FROM AUTHOR]

The surface plasmon resonance (SPR) technique has been widely applied to biosensing technologies for the rapid quantification of biomolecules without enzyme and fluorescent labeling. However, the conventional prism-coupling SPR method generally has a detection area of a few mm2, and the large contribution of the background signal forms a barrier to highly sensitive detection. Based on a highly spatially resolved SPR method, the present study constructed a scanning GC-SPR imaging instrument using an objective lens with a high numerical aperture and a plasmonic chip that could be used for grating-coupled SPR. Focusing light on the diffraction limit can suppress background signals and improve detection sensitivity. SPR imaging can also be performed by scanning a focal spot. Using this method, the refractive index of a mixture of water and dimethyl sulfoxide was measured with a detection accuracy of 2.43 × 10−3 RIU. Polydopamine films prepared with a thickness of <5 nm were also measured, and each film thickness was evaluated with high sensitivity from the effective refractive index detected in a small area of <1 µm2. [ABSTRACT FROM AUTHOR]

We report an experimental study of surface acoustic wave (SAW) localization and propagation in random metasurfaces composed of Al scatters using pump–probe spectroscopy. Thanks to this technique, wideband high frequency acoustic modes are generated, and their dynamical propagation directly from inside of the media with a high (micrometric) spatial resolution is enabled. During SAW propagation, part of the acoustic wavefront energy is trapped within free areas between the scatterers, acting as cavities. The spectral content of the localized modes of a few GHz is found to depend on the shape and size of the cavities but also on the landscape seen by the wave during its propagation before arriving inside them. The experimental results are supported by numerical simulations using the finite element method. This study is the phononic part of a more global research on the co-localization of elastic and optical waves on random metasurfaces, with the main objective of enhancing the photon–phonon interaction. Applications could range from the design of acousto-optic modulators to ultrasensitive sensors. [ABSTRACT FROM AUTHOR]

Multiple scattering poses a fundamental limitation in deep imaging, especially for high-resolution optical imaging methods. The amalgamation of reflection matrix measurements and optical coherence tomography (OCT) has afforded significant advantages for deep imaging through highly scattering media. To empirically exhibit the superior performance of reflection matrix OCT (RMOCT), this study proposes a unique method to ascertain the actual resolutions at each imaging point. In contrast to conventional theoretical lateral resolutions, these resolutions are derived by applying time-reversal decomposition to the time-gated reflection matrix. Moreover, the concept of contribution rate, which quantifies the imaging contributions for each point, is introduced by considering the local imaging point itself and its neighboring points. The contribution rate provides a quantitative evaluation of the imaging quality afforded by a system. To the best of our knowledge, this study represents the comprehensive assessment of the practical performance of RMOCT in terms of actual resolving power and imaging quality. [ABSTRACT FROM AUTHOR]

Whether single-molecule trajectories, observed experimentally or in molecular simulations, can be described using simple models such as biased diffusion is a subject of considerable debate. Memory effects and anomalous diffusion have been reported in a number of studies, but directly inferring such effects from trajectories, especially given limited temporal and/or spatial resolution, has been a challenge. Recently, we proposed that this can be achieved with information-theoretical analysis of trajectories, which is based on the general observation that non-Markov effects make trajectories more predictable and, thus, more "compressible" by lossless compression algorithms. Toy models where discrete molecular states evolve in time were shown to be amenable to such analysis, but its application to continuous trajectories presents a challenge: the trajectories need to be digitized first, and digitization itself introduces non-Markov effects that depend on the specifics of how trajectories are sampled. Here we develop a milestoning-based method for information-theoretical analysis of continuous trajectories and show its utility in application to Markov and non-Markov models and to trajectories obtained from molecular simulations. [ABSTRACT FROM AUTHOR]

Atomistic simulations of biological processes offer insights at a high level of spatial and temporal resolution, but accelerated sampling is often required for probing timescales of biologically relevant processes. The resulting data need to be statistically reweighted and condensed in a concise yet faithful manner to facilitate interpretation. Here, we provide evidence that a recently proposed approach for the unsupervised determination of optimized reaction coordinate (RC) can be used for both analysis and reweighting of such data. We first show that for a peptide interconverting between helical and collapsed configurations, the optimal RC permits efficient reconstruction of equilibrium properties from enhanced sampling trajectories. Upon RC-reweighting, kinetic rate constants and free energy profiles are in good agreement with values obtained from equilibrium simulations. In a more challenging test, we apply the method to enhanced sampling simulations of the unbinding of an acetylated lysine-containing tripeptide from the bromodomain of ATAD2. The complexity of this system allows us to investigate the strengths and limitations of these RCs. Overall, the findings presented here underline the potential of the unsupervised determination of reaction coordinates and the synergy with orthogonal analysis methods, such as Markov state models and SAPPHIRE analysis. [ABSTRACT FROM AUTHOR]

Rationale: Matrix‐assisted laser desorption/ionisation‐mass spectrometry imaging (MALDI‐MSI) is a powerful label‐free technique for biomolecule detection (e.g., lipids), within tissue sections across various biological species. However, despite its utility in many applications, the nematode Caenorhabditis elegans is not routinely used in combination with MALDI‐MSI. The lack of studies exploring spatial distribution of biomolecules in nematodes is likely due to challenges with sample preparation. Methods: This study developed a sample preparation method for whole intact nematodes, evaluated using cryosectioning of nematodes embedded in a 10% gelatine solution to obtain longitudinal cross sections. The slices were then subjected to MALDI‐MSI, using a RapifleX Tissuetyper in positive and negative polarities. Samples were also prepared for liquid chromatography‐tandem mass spectrometry (LC‐MS/MS) analysis using an Exploris 480 coupled to a HPLC Vanquish system to confirm the MALDI‐MSI results. Results: An optimised embedding method was developed for longitudinal cross‐sectioning of individual worms. To obtain longitudinal cross sections, nematodes were frozen at −80°C so that all worms were rod shaped. Then, the samples were defrosted and transferred to a 10% gelatine matrix in a cryomold; the worms aligned, and the whole cryomold submerged in liquid nitrogen. Using MALDI‐MSI, we were able to observe the distribution of lipids within C. elegans, with clear differences in their spatial distribution at a resolution of 5 μm. To confirm the lipids from MALDI‐MSI, age‐matched nematodes were subjected to LC‐MS/MS. Here, 520 lipids were identified using LC‐MS/MS, indicating overlap with MALDI‐MSI data. Conclusions: This optimised sample preparation technique enabled (un)targeted analysis of spatially distributed lipids within individual nematodes. The possibility to detect other biomolecules using this method thus laid the basis for prospective preclinical and toxicological studies on C. elegans. [ABSTRACT FROM AUTHOR]

Developing real‐time, dynamic, and in situ analytical methods with high spatial and temporal resolutions is crucial for exploring biochemical processes in the brain. Although in vivo electrochemical methods based on carbon fiber (CF) microelectrodes are effective in monitoring neurochemical dynamics during physiological and pathological processes, complex post modification hinders large‐scale productions and widespread neuroscience applications. Herein, we develop a general strategy for the in situ engineering of carbon‐based materials to mass‐produce functional CFs by introducing polydopamine to anchor zeolitic imidazolate frameworks as precursors, followed by one‐step pyrolysis. This strategy demonstrates exceptional universality and design flexibility, overcoming complex post‐modification procedures and avoiding the delamination of the modification layer. This simplifies the fabrication and integration of functional CF‐based microelectrodes. Moreover, we design highly stable and selective H+, O2, and ascorbate microsensors and monitor the influence of CO2 exposure on the O2 content of the cerebral tissue during physiological and ischemia‐reperfusion pathological processes. [ABSTRACT FROM AUTHOR]

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Copyright of Technisches Messen is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

SUMMARY: Mass spectrometry imaging (MSI) has become increasingly popular in plant science due to its ability to characterize complex chemical, spatial, and temporal aspects of plant metabolism. Over the past decade, as the emerging and unique features of various MSI techniques have continued to support new discoveries in studies of plant metabolism closely associated with various aspects of plant function and physiology, spatial metabolomics based on MSI techniques has positioned it at the forefront of plant metabolic studies, providing the opportunity for far higher resolution than was previously available. Despite these efforts, profound challenges at the levels of spatial resolution, sensitivity, quantitative ability, chemical confidence, isomer discrimination, and spatial multi‐omics integration, undoubtedly remain. In this Perspective, we provide a contemporary overview of the emergent MSI techniques widely used in the plant sciences, with particular emphasis on recent advances in methodological breakthroughs. Having established the detailed context of MSI, we outline both the golden opportunities and key challenges currently facing plant metabolomics, presenting our vision as to how the enormous potential of MSI technologies will contribute to progress in plant science in the coming years. [ABSTRACT FROM AUTHOR]

Photon counting detector CT (PCD-CT) is the newest major development in CT technology and has been commercially available since 2021. It offers major technological advantages over current standard-of-care energy integrating detector CT (EID-CT) including improved spatial resolution, improved iodine contrast to noise ratio, multi-energy imaging, and reduced noise. This article serves as a foundational basis to the technical approaches and concepts of PCD-CT technology with primary emphasis on detector technology in direct comparison to EID-CT. The article also addresses current technological challenges to PCD-CT with particular attention to cross talk and its causes (e.g., Compton scattering, fluorescence, charge sharing, K-escape) as well as pile-up. [ABSTRACT FROM AUTHOR]

One of the challenges in global change research is the significant uncertainty in global historical land use and land cover (LUCC) datasets, which are widely used as foundational data. In addition to the regional cropland area reconstructions, improving the grid allocation method is another feasible way to raise the reliability of historical LUCC data. In this study, an integrated reconstruction of the national cropland areas over the past 200 years was developed for 36 European countries. After that, the allocation algorithm was built using physiogeographic variables and historical city sites for accounting for land suitability and cultivation preferences, respectively. Finally, cropland data in Europe with a spatial resolution of 5′×5′ at five time sections from AD 1800 to 2000 were generated using the optimal allocation algorithm in accordance with the stages of the regional history. The results were as follows: (1) The dominant factors governing the distribution of croplands in Europe vary at different agricultural stages, but the results can be merged together. Land suitability was more optimal for allocation during the modern agricultural stage (AD 1950 and 2000); the priority index combined with land suitability and cultivation preference was more reasonable for allocation during the traditional agricultural stage (AD 1800). The average of the allocations by priority index and the land suitability could be adopted as the allocation results during the transitional stage (AD 1850 and 1900) because the grids for absolute differences within ±10 and ±20 percentage points between the results obtained from the above two allocations were above 80% and 95%, respectively, which means the two allocation results could be merged. (2) Over the past 200 years, the total cropland area in Europe first increased to a peak in AD 1900 and then decreased. Spatially, the centre of the higher cropland fraction shifted from the western part of Europe in AD 1800 to the eastern part of the continent after AD 1950. (3) Both the cropland area and the spatial distribution in this study are more reasonable than the global dataset HYDE3.2. [ABSTRACT FROM AUTHOR]

Aim: The scale of environmental data is often defined by their extent (spatial area, temporal duration) and resolution (grain size, temporal interval). Although describing climate data scale via these terms is appropriate for most meteorological applications, for ecology and biogeography, climate data of the same spatiotemporal resolution and extent may differ in their relevance to an organism. Here, we propose that climate proximity, or how well climate data represent the actual conditions that an organism is exposed to, is more important for ecological realism than the spatiotemporal resolution of the climate data. Location: Temperature comparison in nine countries across four continents; ecological case studies in Alberta (Canada), Sabah (Malaysia) and North Carolina/Tennessee (USA). Time Period: 1960–2018. Major Taxa Studied: Case studies with flies, mosquitoes and salamanders, but concepts relevant to all life on earth. Methods: We compare the accuracy of two macroclimate data sources (ERA5 and WorldClim) and a novel microclimate model (microclimf) in predicting soil temperatures. We then use ERA5, WorldClim and microclimf to drive ecological models in three case studies: temporal (fly phenology), spatial (mosquito thermal suitability) and spatiotemporal (salamander range shifts) ecological responses. Results: For predicting soil temperatures, microclimf had 24.9% and 16.4% lower absolute bias than ERA5 and WorldClim respectively. Across the case studies, we find that increasing proximity (from macroclimate to microclimate) yields a 247% improvement in performance of ecological models on average, compared to 18% and 9% improvements from increasing spatial resolution 20‐fold, and temporal resolution 30‐fold respectively. Main Conclusions: We propose that increasing climate proximity, even if at the sacrifice of finer climate spatiotemporal resolution, may improve ecological predictions. We emphasize biophysically informed approaches, rather than generic formulations, when quantifying ecoclimatic relationships. Redefining the scale of climate through the lens of the organism itself helps reveal mechanisms underlying how climate shapes ecological systems. [ABSTRACT FROM AUTHOR]

Purpose: Lens power profiles can provide valuable insights on the imposed optical defocus and visual experience of contact lens wearers, especially in the context of myopia control. This study measured the refractive power profiles of multifocal soft contact lenses (MFCLs) currently used or that have the potential for use in myopia control using high spatial resolution aberrometry. The instrument's repeatability for determining MFCLs power profiles was also assessed. Method: The power profiles of 10 MFCLs of various designs (centre‐distance, centre‐near and extended depth of focus) were measured using the Lambda‐X NIMOEVO, a phase shifting Schlieren‐based device. Power profiles were graphically expressed as measured power at each chord position and the maximum add power was calculated. The repeatability of the NIMOEVO was expressed as the within‐subject standard deviation at each chord position for a subset of five MFCLs. Results: The measured distance powers differed from nominal powers for more than half of the MFCLs with a definable distance zone. There were variations in the chord position of the distance and near correction zones, rate of power transitions and calculated maximum add between the MFCLs which did not depend on lens design. For half of the MFCLs, the power profile shape was inconsistent between different nominal back vertex powers of the same design. The repeatability of the NIMOEVO was dependent on the lens design, with designs featuring faster rates of power change exhibiting worse repeatability. Conclusions: Significant differences in MFCL power profiles were found which were not adequately represented in labelling. This is likely due to the small number of parameters used to define lens power characteristics. Eye health care practitioners should be aware of potential differences in power profiles between different MFCLs, which will impact the retinal defocus introduced during lens wear and the wearer's visual experience. [ABSTRACT FROM AUTHOR]

Summary: The accurate characterisation of centreline segregation requires precise measurements of composition variations over large length scales (10−1$^{-1}$m${\rm {m}}$) across the centreline of the cast product, while having high resolution, sufficient to quantify the significant composition variations between dendrites due to microsegregation at very small length scales (10−5m$^{-5}{\rm {m}}$). This study investigates the potential of a novel microscopy technique, named Synchrotron Micro X‐ray Flurorescence (SMXRF), to generate large‐scale high‐resolution segregation maps from a steel sample taken from a thin slab caster. Two methods, Point Analysis and Regression Analysis, are proposed for SMXRF data calibration. By comparing with the traditional Laser‐Induced Breakdown Spectroscopy (LIBS), and Electron Probe Micro Analyser (EPMA) techniques, we show that SMXRF is successful in quantitative characterisation of centreline segregation. Over large areas (e.g. 12 ×$\times$ 16 mm2${\rm {mm}}^2$) and at high resolution (10–50 μm$\mu\text{m}$ pixel size) various techniques yield comparable outcomes in terms of composition maps and solute profiles. The findings also highlight the importance of both high spatial resolution and large field of view to have a quantitative, accurate, and efficient measurement tool to investigate segregation phenomena. [ABSTRACT FROM AUTHOR]

In musculoskeletal imaging, CT is used in a wide range of indications, either alone or in a synergistic approach with MRI. While MRI is the preferred modality for the assessment of soft tissues and bone marrow, CT excels in the imaging of high-contrast structures, such as mineralized tissue. Additionally, the introduction of dual-energy CT in clinical practice two decades ago opened the door for spectral imaging applications. Recently, the advent of photon-counting detectors (PCDs) has further advanced the potential of CT, at least in theory. Compared to conventional energy-integrating detectors (EIDs), PCDs provide superior spatial resolution, reduced noise, and intrinsic spectral imaging capabilities. This review briefly describes the technical advantages of PCDs. For each technical feature, the corresponding applications in musculoskeletal imaging will be discussed, including high-spatial resolution imaging for the assessment of bone and crystal deposits, low-dose applications such as whole-body CT, as well as spectral imaging applications including the characterization of crystal deposits and imaging of metal hardware. Finally, we will highlight the potential of PCD-CT in emerging applications, underscoring the need for further preclinical and clinical validation to unleash its full clinical potential. [ABSTRACT FROM AUTHOR]

Accurate quantification of snow cover facilitates the prediction of snowmelt runoff, the assessment of freshwater availability, and the analysis of Earth's energy balance. Existing fractional snow cover (FSC) data, however, often suffer from limitations such as spatial and temporal gaps, compromised accuracy, and coarse spatial resolution. These limitations significantly hinder the ability to monitor snow cover dynamics effectively. To address these formidable challenges, this study introduces a novel data fusion framework specifically designed to generate high-resolution (1 km) daily FSC estimation across vast regions like North America, regardless of weather conditions. It achieved this by effectively integrating the complementary spatiotemporal characteristics of both coarse- and fine-resolution FSC data through a multi-stage processing pipeline. This pipeline incorporates innovative strategies for bias correction, gap filling, and consideration of dynamic characteristics of snow cover, ultimately leading to high accuracy and high spatiotemporal completeness in the fused FSC data. The accuracy of the fused FSC data was thoroughly evaluated over the study period (September 2015 to May 2016), demonstrating excellent consistency with independent datasets, including Landsat-derived FSC (total 24 scenes; RMSE=6.8–18.9 %) and ground-based snow observations (14,350 stations). Notably, the fused data outperforms the widely used Interactive Multi-sensor Snow and Ice Mapping System (IMS) daily snow cover extent data in overall accuracy (0.92 vs. 0.91), F1_score (0.86 vs. 0.83), and Kappa coefficient (0.80 vs. 0.77). Furthermore, the fused FSC data exhibits superior performance in accurately capturing the intricate daily snow cover dynamics compared to IMS data, as confirmed by superior agreement with ground-based observations in four snow-cover phenology metrics. In conclusion, the proposed data fusion framework offers a significant advancement in snow cover monitoring by generating high-accuracy, spatiotemporally complete daily FSC maps that effectively capture the spatial and temporal variability of snow cover. These FSC datasets hold substantial value for climate projections, hydrological studies, and water management at both global and regional scales. [ABSTRACT FROM AUTHOR]

Hyperspectral (HS) satellites like PRISMA (PRecursore IperSpettrale della Missione Applicativa) offer remarkable capabilities, yet they are constrained by a relatively coarse spatial resolution, curbing their efficacy in those applications that require pinpoint accuracy. Here we propose a fusion process, aimed at the enhancement of PRISMA HS spatial resolution by using the spatial and spectral information of Sentinel-2 multispectral (MS) data (HS-MS fusion process), validated against four airborne HS flights simultaneous to satellite overpasses on different land use distributions. Adopting the PRISMA panchromatic (PAN) image, the proposed solution was also compared with the results of a HS-PAN pansharpening process. A two-steps operational workflow is proposed, based on two state-of-the-art and open-source algorithms. The first step consisted of the geocoding of PRISMA L2 products using Senintel-2 as reference and was accomplished with the phase-based algorithm implemented in AROSICS (Automated and Robust Open-Source Image Co-registration Software). The geometric displacement in L2 data was found to be between 80 m and 250 m, irregularly spatially distributed throughout the same scene and among scenes, and it was corrected by means of thousands of regularly spatially distributed tie points. A second-order polynomial transformation function was integrated in the algorithm. The second step consisted of employing the HySure (HS Super resolution) fusion algorithm to perform both the HS-MS fusion and the HS-PAN pansharpening, returning a PRISMA HS improved dataset with a spatial resolution of 10 m and 5 m, respectively. Four different per-band accuracy metrics were used to evaluate the accuracy of both products against airborne data. Overall, HS-MS data achieved increased accuracy in all validation metrics, i.e. + 28 % (root mean square error, RMSE), +23 % (spectral angle mapper, SAM), +7% (peak signal-to-noise ratio, PSNR) and + 11 % (universal image quality index, UIQI), with respect of HS-PAN data. These outcomes showed that using the spectral information of Sentinel-2 both spectral and spatial patterns were reconstructed more consistently in three different urban and rural scenarios, avoiding the presence of blur and at-edge artefacts as opposed to HS-PAN pansharpening, therefore suggesting an optimal strategy for satellite HS data resolution enhancement. [ABSTRACT FROM AUTHOR]

State-of-the-art models in semantic segmentation primarily operate on single, static images, generating corresponding segmentation masks. This one-shot approach leaves little room for error correction, as the models lack the capability to integrate multiple observations for enhanced accuracy. Inspired by work on semantic change detection, we address this limitation by introducing a methodology that leverages a sequence of observables generated for each static input image. By adding this "temporal" dimension, we exploit strong signal correlations between successive observations in the sequence to reduce error rates. Our framework, dubbed SSG2 (Semantic Segmentation Generation 2), employs a dual-encoder, single-decoder base network augmented with a sequence model. The base model learns to predict the set intersection, union, and difference of labels from dual-input images. Given a fixed target input image and a set of support images, the sequence model builds the predicted mask of the target by synthesizing the partial views from each sequence step and filtering out noise. We evaluate SSG2 across four diverse datasets: UrbanMonitor, featuring orthoimage tiles from Darwin, Australia with four spectral bands at 0.2 m spatial resolution and a surface model; ISPRS Potsdam, which includes true orthophoto images with multiple spectral bands and a 5 cm ground sampling distance; ISPRS Vahingen, which also includes true orthophoto images and a 9 cm ground sampling distance; and ISIC2018, a medical dataset focused on skin lesion segmentation, particularly melanoma. The SSG2 model demonstrates rapid convergence within the first few tens of epochs and significantly outperforms UNet-like baseline models with the same number of gradient updates. However, the addition of the temporal dimension results in an increased memory footprint. While this could be a limitation, it is offset by the advent of higher-memory GPUs and coding optimizations. Our code is available at https://github.com/feevos/ssg2. [ABSTRACT FROM AUTHOR]

White matter, a densely packed collection of myelinated axons, plays an essential part in neural networks. With high spatial resolution and deep penetration, multi-photon microscopy (MPM) is promising for white matter imaging in animal models in vivo. The third harmonic generation (THG) signal can be generated from white matter, but the bottom part of the white matter layer generates weak THG due to its high scattering. Here, we demonstrate an in vivo labeling and imaging technology, capable of visualizing the white matter layer in the mouse brain, combining fluorescence labeling with MitoTracker Red and three-photon fluorescence (3PF) microscopy excited at the 1700 nm window. 3PF signals are several times higher than THG signals, resulting in deeper imaging of the white matter layer with the former. Our results indicate that 3PF microscopy is a promising technology for white matter imaging in the deep brain in vivo. [ABSTRACT FROM AUTHOR]

Current European transport demand models following the classical four-step approach are less suitable for analysing the traffic volumes on inter-regional road infrastructure with relevant demand of regional trips, as they consider only about 10% of the trip demand with passenger cars. Mainly due to runtime problems, these models are limited to operation at the NUTS-3 level. This level comprises around 1500 regions for Europe with an average diameter of about 50 km. However, more than 90% of the trips are shorter than 50 km and are, therefore, not adequately considered in the trip distribution model and the trip matrix. Computing this matrix at a higher spatial resolution, such as the LAU-2 level, is not possible as the runtime of the overall model and the size of the trip matrix increase quadratically with the number of travel zones. In the HIPAT model, this obstacle is overcome by an innovative concept operating at different hierarchical levels. This reduces the complexity of the trip matrix, such that the HIPAT model can be applied at large scale for 150,000 travel zones without any runtime problems. This is demonstrated by a prototype implementation for a case study that handles 33,000 travel zones in two minutes. In addition, the limitations of applying NUTS-3-based travel zones for transport modelling are shown: 94.6% of the trips are shorter than the average diameter of the travel zones (50 km) and are therefore not correctly represented by the model. Smaller travel zones decrease this number and provide a better basis for analysing infrastructure policies and, ultimately, for decision-making. • Large-scale application of the four-step model without runtime problems. • One consistent EU transport demand model for long-distance and short distance trips. • HIPAT bases on EU transport policy assessment model HIGH-TOOL and ETISplus data. • Smaller travel zones yield to superior model results. • HIPAT was successfully applied for about 33,000 travel zones in a case study. [ABSTRACT FROM AUTHOR]

Flat objects like electronic boards are challenging samples for high-resolution X-ray computed tomography scanning because their largest dimension significantly limits the magnification using circular trajectory scans. One way to improve spatial resolution for such samples is to utilize variable zoom trajectory. During variable zoom trajectory scanning, the source-to-object distance changes during the 360° rotation to maximize the magnification in the projections. Here, we propose an automatic variable zoom trajectory generation algorithm for arbitrary object and region of interest (ROI). We analyze how such a trajectory can enhance resolution in different cases and how isotropic is the resolution in the reconstructed volume. We demonstrate that the resolution can be improved without destroying the sample. However, the improvement is manifested mainly in directions in which we achieved the highest magnification in the projection. [ABSTRACT FROM AUTHOR]

• Introducing the downscaling algorithm to the study of sea surface temperature for the first time. • Comparative validation using MGWR and GWR downscaling algorithms. • Converted SST products with 25 km spatial resolution to 5 km spatial resolution. • All-weather high spatial resolution sea surface temperature data were obtained. • It is useful for the accuracy improvement of SST product for FY-3C microwave imager. Sea surface temperature (SST) serves as a vital meteorological parameter, exerting considerable influence on climate change and the Earth's oceanic system. To address the limitation of microwave sensors in providing all-weather and high spatial resolution SST products, we focus on utilizing FY-3C/ Microwave Radiation Imager (MWRI) SST, sea surface wind speed, and chlorophyll concentration data from 12 periods in the South China Sea and Yellow-Bohai Sea. It further develops a spatial downscaling algorithm for MWRI SST products based on the Multiscale Geographically Weighted Regression (MGWR) method. The results show that the MGWR-based downscaling conversion function adeptly unveils distinct interaction relationships between different SST state parameters and SST, and sea surface wind speed exhibits a global impact on SST distribution, while longitude, latitude, and chlorophyll mass concentration have a localized effect on SST. Moreover, the downscaled 5 km resolution SST data derived from the MGWR algorithm boasts enhanced spatial texture, compensating for the limitations of infrared data. Finally, the downscaled MWRI SST is evaluated by FY-3C/VIRR SST data. We find that the coefficient of determination (R2) of both is greater than 0.86, and the root mean square error (RMSE) and mean absolute error (MAE) are less than 1.29 K and 1 K, respectively. [ABSTRACT FROM AUTHOR]

The temperature of melt blowing (MB) and melt spun fibers is frequently measured using infrared thermography (IRT). However, measurements are affected by the size and curvature of the fiber and by reflected radiation from the nozzle. A procedure was developed to obtain accurate measurements of fiber temperature, which corrects fiber size, fiber curvature, and reflected radiation. This procedure is more general than the ones used so far to correct fiber temperature because it corrects the three abovementioned factors using a single correction formula, this being the first time that fiber temperature correction for reflected radiation has been accounted for. It is also more accurate because it uses the local fiber diameter to correct fiber curvature, instead of mean fiber diameter. The procedure was used to measure the temperature of MB adhesive fibers produced by two multi-hole nozzle designs, the results indicating that, in melt blowing applications, the distortion caused by fiber curvature and reflected radiation on the measurement proves to be far more significant than that caused by fiber size, while correction generally leads to an increase in fiber temperature. Considerations as to the effect of different parameters on temperature correction, as well as the quality of thermographic images, are also provided throughout the text. The conclusions emerging from this study allow more accurate temperature measurements of melt blown and melt spun fibers to be obtained. [ABSTRACT FROM AUTHOR]

To develop acceleration strategies for 3D multi-slab diffusion weighted imaging (3D ms-DWI) for enabling applications that require simultaneously high spatial (1 mm isotropic) and angular (> 30 directions) resolutions. 3D ms-DWI offers high SNR-efficiency, with the ability to achieve high isotropic spatial resolution, yet suffers from long scan-times for studies requiring high angular resolutions. We develop 6D k-q space acceleration strategies to reduce the scan-time. Specifically, we develop non-uniform 3D k y - k z under-sampling employing a shot-selective 2D CAIPI sampling approach. To achieve inter-shot phase-compensation, 2D navigators were employed that utilize the same CAIPI trajectory. An iterative model-based 3D multi-shot reconstruction was designed by incorporating phase into the forward encoding process. Additionally, the shot-selective non-uniform k y - k z CAIPI acceleration was randomized along the q-dimension. The 3D model-based multi-shot reconstruction is then extended to a joint reconstruction that simultaneously reconstructs all the q-space points, with the help of a spatial total variation and deep-learned q-space regularization. The proposed reconstruction is shown to achieve adequate phase-compensation in both 2D CAIPI accelerated and additional k y - k z under-sampled cases. Using retrospective under-sampling experiments, we show that k-q accelerations close a factor of 12 can be achieved with a reconstruction error < 3% for both single and multi-shell data. This translates to a scan-time reduction by 3-fold for experiments with simultaneously high spatial and angular resolutions. The proposed method facilitates the utilization of 3D ms-DWI for simultaneously high k-q resolution applications with close to 3× reduced scan-time. [ABSTRACT FROM AUTHOR]

Spatially resolved capacitance-based stress self-sensing in unmodified concrete has been demonstrated. The spatial resolution is 45 mm in one dimension, which is in the direction of the capacitance measurement. Parallel coplanar component electrodes (aluminum, 5-mm wide), attached to the concrete using double-sided adhesive tape) separated by 45 mm are used to measure the in-plane capacitance in the direction perpendicular to the length of the electrodes. Combinations of component electrodes are electrically connected to form an electrode. The capacitance ranges from ∼200 pF to ∼750 pF. The greater is the number of component electrodes in an electrode, the higher is the capacitance. The compressive loading is applied at selected areas located between adjacent component electrodes. The stress (defined as load divided by the 300 ×300-mm2 concrete area) is up to 3000 Pa. The load decreases the capacitance monotonically and reversibly. The fractional decrease in capacitance ranges from ∼0.1 % to ∼0.5 %. More spatially concentrated loading, as for loading near the edges of the specimen, gives greater fractional decrease in capacitance. The capacitance decreases with increasing inter-electrode distance. Embedded steel rebars with a 20.0-mm concrete cover do not affect the capacitance or capacitance-based sensing. • Spatially resolved structural self-sensing of stress is reported. • It involves capacitance measurement, as shown for unmodified concrete. • Parallel coplanar component electrodes (aluminum strips) 45 mm apart are used. • Component electrodes are electrically connected to form a composite electrode. • The compressive stress reduces the capacitance reversibly and monotonically. [ABSTRACT FROM AUTHOR]

Objectives: To detect ultrasonographic anatomical alterations in all the skin layers in patients with vitiligo. Methods: A prospective observational color Doppler ultrasound study was performed in nonsegmental face and/or neck vitiligo patients without a history of previous treatments. Two sites, a lesional area and a contralateral clinically healthy region, were ultrasonographically studied and compared in the same patient. All cases were studied in high‐frequency (24 MHz) and ultra‐high‐frequency (70 MHz) ultrasound devices with the highest axial spatial resolution available in the market. Demographic data of the sample, ultrasound grayscale, and color Doppler features were recorded and analyzed. Results: Ten patients met the study criteria (60% females; mean age 49 years). All cases presented ultrasonographic undulation of the epidermis in the affected zones vs 50% in the healthy control regions, being more prominent in the vitiligo areas. Eighty percent demonstrated intense hypoechoic thin plaques in the upper dermis (subepidermal). All vitiligo areas presented thickening and hypoechogenicity of the regional hair follicles and/or pilosebaceous units. Ninety percent showed prominent sebaceous glands, and 20% demonstrated a hypoechoic cap surrounding the sebaceous glands in the lesional areas. Dermal hypervascularity was detected in 100% of the affected regions and 40% of the clinically healthy areas. Conclusion: Ultrasound can identify subclinical inflammatory cutaneous patterns in the epidermis, dermis, hair follicles, pilosebaceous units, and sebaceous glands in vitiligo. This noninvasive information can support early detection, monitoring, and research, including the clinical trials of drugs used to manage this devastating disease. [ABSTRACT FROM AUTHOR]

Background: For time‐consuming diffusion‐weighted imaging (DWI) of the breast, deep learning‐based imaging acceleration appears particularly promising. Purpose: To investigate a combined k‐space‐to‐image reconstruction approach for scan time reduction and improved spatial resolution in breast DWI. Study Type: Retrospective. Population: 133 women (age 49.7 ± 12.1 years) underwent multiparametric breast MRI. Field Strength/Sequence: 3.0T/T2 turbo spin echo, T1 3D gradient echo, DWI (800 and 1600 sec/mm2). Assessment: DWI data were retrospectively processed using deep learning‐based k‐space‐to‐image reconstruction (DL‐DWI) and an additional super‐resolution algorithm (SRDL‐DWI). In addition to signal‐to‐noise ratio and apparent diffusion coefficient (ADC) comparisons among standard, DL‐ and SRDL‐DWI, a range of quantitative similarity (e.g., structural similarity index [SSIM]) and error metrics (e.g., normalized root mean square error [NRMSE], symmetric mean absolute percent error [SMAPE], log accuracy error [LOGAC]) was calculated to analyze structural variations. Subjective image evaluation was performed independently by three radiologists on a seven‐point rating scale. Statistical Tests: Friedman's rank‐based analysis of variance with Bonferroni‐corrected pairwise post‐hoc tests. P < 0.05 was considered significant. Results: Both DL‐ and SRDL‐DWI allowed for a 39% reduction in simulated scan time over standard DWI (5 vs. 3 minutes). The highest image quality ratings were assigned to SRDL‐DWI with good interreader agreement (ICC 0.834; 95% confidence interval 0.818–0.848). Irrespective of b‐value, both standard and DL‐DWI produced superior SNR compared to SRDL‐DWI. ADC values were slightly higher in SRDL‐DWI (+0.5%) and DL‐DWI (+3.4%) than in standard DWI. Structural similarity was excellent between DL‐/SRDL‐DWI and standard DWI for either b value (SSIM ≥ 0.86). Calculation of error metrics (NRMSE ≤ 0.05, SMAPE ≤ 0.02, and LOGAC ≤ 0.04) supported the assumption of low voxel‐wise error. Data Conclusion: Deep learning‐based k‐space‐to‐image reconstruction reduces simulated scan time of breast DWI by 39% without influencing structural similarity. Additionally, super‐resolution interpolation allows for substantial improvement of subjective image quality. Evidence Level: 4 Technical Efficacy: Stage 1 [ABSTRACT FROM AUTHOR]

Purpose: To demonstrate the feasibility of zigzag sampling for 3D rapid hyperpolarized 129Xe ventilation MRI in human. Methods: Zigzag sampling in one direction was combined with gradient‐recalled echo sequence (GRE‐zigzag‐Y) to acquire hyperpolarized 129Xe ventilation images. Image quality was compared with a balanced SSFP (bSSFP) sequence with the same spatial resolution for 12 healthy volunteers (HVs). For another 8 HVs and 9 discharged coronavirus disease 2019 subjects, isotropic resolution 129Xe ventilation images were acquired using zigzag sampling in two directions through GRE‐zigzag‐YZ. 129Xe ventilation defect percent (VDP) was quantified for GRE‐zigzag‐YZ and bSSFP acquisitions. Relationships and agreement between these VDP measurements were evaluated using Pearson correlation coefficient (r) and Bland–Altman analysis. Results: For 12 HVs, GRE‐zigzag‐Y and bSSFP required 2.2 s and 10.5 s, respectively, to acquire 129Xe images with a spatial resolution of 3.96 × 3.96 × 10.5 mm3. Structural similarity index, mean absolute error, and Dice similarity coefficient between the two sets of images and ventilated lung regions were 0.85 ± 0.03, 0.0015 ± 0.0001, and 0.91 ± 0.02, respectively. For another 8 HVs and 9 coronavirus disease 2019 subjects, 129Xe images with a nominal spatial resolution of 2.5 × 2.5 × 2.5 mm3 were acquired within 5.5 s per subject using GRE‐zigzag‐YZ. VDP provided by GRE‐zigzag‐YZ was strongly correlated (R2 = 0.93, p < 0.0001) with that generated by bSSFP with minimal biases (bias = −0.005%, 95% limit‐of‐agreement = [−0.414%, 0.424%]). Conclusion: Zigzag sampling combined with GRE sequence provides a way for rapid 129Xe ventilation imaging. [ABSTRACT FROM AUTHOR]

Purpose: To develop a highly accelerated multi‐echo spin‐echo method, TEMPURA, for reducing the acquisition time and/or increasing spatial resolution for kidney T2 mapping. Methods: TEMPURA merges several adjacent echoes into one k‐space by either combining independent echoes or sharing one echo between k‐spaces. The combined k‐space is reconstructed based on compressed sensing theory. Reduced flip angles are used for the refocusing pulses, and the extended phase graph algorithm is used to correct the effects of indirect echoes. Two sequences were developed: a fast breath‐hold sequence; and a high‐resolution sequence. The performance was evaluated prospectively on a phantom, 16 healthy subjects, and two patients with different types of renal tumors. Results: The fast TEMPURA method reduced the acquisition time from 3–5 min to one breath‐hold (18 s). Phantom measurements showed that fast TEMPURA had a mean absolute percentage error (MAPE) of 8.2%, which was comparable to a standardized respiratory‐triggered sequence (7.4%), but much lower than a sequence accelerated by purely k‐t undersampling (21.8%). High‐resolution TEMPURA reduced the in‐plane voxel size from 3 × 3 to 1 × 1 mm2, resulting in improved visualization of the detailed anatomical structure. In vivo T2 measurements demonstrated good agreement (fast: MAPE = 1.3%–2.5%; high‐resolution: MAPE = 2.8%–3.3%) and high correlation coefficients (fast: R = 0.85–0.98; high‐resolution: 0.82–0.96) with the standardized method, outperforming k‐t undersampling alone (MAPE = 3.3–4.5%, R = 0.57–0.59). Conclusion: TEMPURA provides fast and high‐resolution renal T2 measurements. It has the potential to improve clinical throughput and delineate intratumoral heterogeneity and tissue habitats at unprecedented spatial resolution. [ABSTRACT FROM AUTHOR]

The L-band vegetation optical depth data garners significant interest for its ability to effectively monitor vegetation, thanks to minimal saturation within this frequency range. However, the existing datasets have limited temporal coverage, constrained by the start of the respective satellite missions. Global L-band equivalent AI-Based Vegetation Optical Depth or GLAB-VOD is a global long-term consistent microwave vegetation optical depth dataset created using machine learning to expand the SMAP-IB VOD dataset temporal coverage from 2015-2020 to 2002-2020. The GLAB-VOD dataset has an 18-day temporal resolution and 25 km spatial resolution on the EASE2 grid and covers 2002-2020. An auxiliary consistent daily brightness temperature product, called GLAB-TB, is developed in parallel and ensures the consistency of the VOD product across time periods with different microwave satellites. As a result of its temporal consistency, this dataset can be used to study long-term global and regional trends in vegetation biomass and utilized in any other applications where long-term consistency is necessary. The GLAB-VOD dataset shows excellent spatial correlation globally when compared with biomass (up to R = 0.92) and canopy height (R = 0.93), outperforming its target dataset, SMAP-IB VOD. [ABSTRACT FROM AUTHOR]

Soil moisture content (SMC) plays a significant role in land surface water and energy cycle and is essential in performing various field-related studies. It is a crucial parameter provided by passive L-band sensors on soil moisture active passive/soil moisture ocean salinity satellite missions at a resolution of ~36–40 km. To obtain inference from the SMC data and apply it to different applications, its study and analysis are required that is achievable using any geographic information systems software. Quantum Geographic Information System (QGIS) is an open-source software with a user-friendly graphical user interface (GUI) and a repository of application-specific plugins. However, no plugin provides SMC or downscales the SMC product for a required location. Q-Daily Arial Image (Q-DAI), the QGIS plugin proposed here, implements a downscaling algorithm to obtain the low-resolution SMC product from SMAP/SMOS at fine resolution using inputs from high-resolution satellite imagery. The plugin is developed by designing a GUI using Qt Creator and defining its functionality using Python. Q-DAI is tested on QGIS 3.16.16 on Windows 10, 8 GB RAM PC and QGIS 3.22 on a macOS Ventura laptop. Q-DAI can be used to obtain high-resolution SMC for any location, and in this article, sample results of Q-DAI implemented for Delhi region data have been shown. [ABSTRACT FROM AUTHOR]

This study demonstrates that out‐of‐area (OOA) property transactions can serve as a proxy for migration. Using micro‐level transaction data, we document that about 35% of migrants make OOA property purchases. The goodness‐of‐fit between migration and OOA purchases is higher for aggregate migration measures and lower for migration flows between disaggregated areas. Furthermore, in most specifications, a one percent increase in OOA purchases is associated with an approximately one percent increase in migration. We characterize the monthly out‐migration from NYC zip codes to surrounding areas after the outbreak of the COVID‐19 pandemic to demonstrate the high temporal and spatial resolution of OOA transaction data. [ABSTRACT FROM AUTHOR]

The molecular phase of supernova-driven outflows originates from the cold, molecular gas in the disc of a star-forming galaxy, and may carry a substantial fraction of the wind mass flux in some galaxies, but it remains poorly understood. Observations of this phase come mostly from very nearby galaxies due its low-surface brightness and covering fraction, and simulations often lack the spatial resolution necessary to resolve it. Here, we analytically estimate the survivability of this phase in order to understand under what conditions a galactic wind can contain a significant molecular phase. We show that the molecular content of outflows is primarily determined by two dimensionless numbers: a generalized Eddington ratio describing the strength of the outflow and the dissociation parameter, an ionization parameter-like quantity describing the strength of the radiation field per baryon. We apply this model to a sample of galaxies and show that, while any molecules entrained in the winds of normal star-forming galaxies should be destroyed close to the galactic disc, the outflows of strong starburst should become increasingly dominated by molecules. [ABSTRACT FROM AUTHOR]

Understansding complex biological systems requires the simultaneous characterization of a large number of interacting components in their native 3D environment with high spatial resolution. Highly-multiplexed Raman imaging is an emerging general strategy for detecting biomarkers with scalable multiplexity and ultra-sensitivity based on a series of stimulated Raman scattering (SRS) techniques. Here we review recent advances in highly-multiplexed Raman imaging and how they contribute to the technological revolution in 3D spatial biology, focusing on the developmental pathway from spectroscopy study to biotechnology invention. We envision highly-multiplexed Raman imaging is taking off, which will greatly facilitate our understanding in biological and medical research fields. [ABSTRACT FROM AUTHOR]

Objective: Positron Emission Tomography (PET) is a well-known imaging technology for the diagnosis, treatment, and monitoring of several diseases. Most PET scanners use a Ring-Shaped Detector Configuration (RSDC), which helps obtain homogeneous image quality but are restricted to an invariable Field-of-View (FOV), scarce spatial resolution, and low sensitivity. Alternatively, few PET systems use Open Detector Configurations (ODC) to permit an accessible FOV adaptable to different target sizes, thus optimizing sensitivity. Yet, to compensate the lack of angular coverage in ODC-PET, developing a detector with high-timing performance is mandatory to enable Time-of-Flight (TOF) techniques during reconstruction. The main goal of this work is to provide a proof of concept PET scanner appropriate for constructing the new generation of ODC-PET suitable for biopsy guidance and clinical intervention during acquisition. The designed detector has to be compact and robust, and its requirements in terms of performance are spatial and time resolutions < 2 mm and < 200 ps, respectively. Methods: The present work includes a simulation study of an ODC-PET based on 2-panels with variable distance. The image quality (IQ) and Derenzo phantoms have been simulated and evaluated. The phantom simulations have also been performed using a ring-shaped PET for comparison purposes of the ODC approach with conventional systems. Then, an experimental evaluation of a prototype detector that has been designed following the simulation results is presented. This study focused on tuning the ASIC parameters and evaluating the scintillator surface treatment (ESR and TiO2), and configuration that yields the best Coincidence Time Resolution (CTR). Moreover, the scalability of the prototype to a module of 64 × 64mm2 and its preliminary evaluation regarding pixel identification are provided. Results: The simulation results reported sensitivity (%) values at the center of the FOV of 1.96, 1.63, and 1.18 for panel distances of 200, 250, and 300 mm, respectively. The IQ reconstructed image reported good uniformity (87%) and optimal CRC values, and the Derenzo phantom reconstruction suggests a system resolution of 1.6–2 mm. The experimental results demonstrate that using TiO2 coating yielded better detector performance than ESR. Acquired data was filtered by applying an energy window of ± 30% at the photopeak level. After filtering, best CTR of 230 ± 2 ps was achieved for an 8 × 8 LYSO pixel block with 2 × 2 × 12mm3 each. The detector performance remained constant after scaling-up the prototype to a module of 64 × 64mm2, and the flood map demonstrates the module's capabilities to distinguish the small pixels; thus, a spatial resolution < 2 mm (pixel size) is achieved. Conclusions: The simulated results of this biplanar scanner show high performance in terms of image quality and sensitivity. These results are comparable to state-of-the-art PET technology and, demonstrate that including TOF information minimizes the image artifacts due to the lack of angular projections. The experimental results concluded that using TiO2 coating provide the best performance. The results suggest that this scanner may be suitable for organ study, breast, prostate, or cardiac applications, with good uniformity and CRC. [ABSTRACT FROM AUTHOR]

Electroencephalography (EEG) is a technique for non‐invasively measuring neuronal activity in the human brain using electrodes placed on the participant's scalp. With the advancement of digital technologies, EEG analysis has evolved over time from the qualitative analysis of amplitude and frequency modulations to a comprehensive analysis of the complex spatiotemporal characteristics of the recorded signals. EEG is now considered a powerful tool for measuring neural processes in the same time frame in which they happen (i.e. the subsecond range). However, it is commonly argued that EEG suffers from low spatial resolution, which makes it difficult to localize the generators of EEG activity accurately and reliably. Today, the availability of high‐density EEG (hdEEG) systems, combined with methods for incorporating information on head anatomy and sophisticated source‐localization algorithms, has transformed EEG into an important neuroimaging tool. hdEEG offers researchers and clinicians a rich and varied range of applications. It can be used not only for investigating neural correlates in motor and cognitive neuroscience experiments, but also for clinical diagnosis, particularly in the detection of epilepsy and the characterization of neural impairments in a wide range of neurological disorders. Notably, the integration of hdEEG systems with other physiological recordings, such as kinematic and/or electromyography data, might be especially beneficial to better understand the neuromuscular mechanisms associated with deconditioning in ageing and neuromotor disorders, by mapping the neurokinematic and neuromuscular connectivity patterns directly in the brain. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim Location Major Taxa Studied Methods Results Main Conclusions The Kunming‐Montreal Global Biodiversity Framework requires that evolutionary histories of species should be considered in conservation planning. The phylogenetic structure of species assemblages quantifies species evolutionary histories and increasingly becomes an endeavour for ecologists. Understanding the geographic patterns of phylogenetic structure of species assemblages and their drivers can provide a fundamental reference for conservation planning. Although several theoretical hypotheses based on the effects of contemporary environment, historical climate change and evolutionary niche conservatism had been widely discussed in previous studies, the relative contributions of these hypotheses on phylogenetic structure of angiosperms, especially herbaceous species, remain debated.East Eurasia.Angiosperms.We compiled distributions of 43,023 angiosperm species in east Eurasia at spatial resolution (100 × 100 km2). Using this newly compiled database and a species‐level phylogeny, we estimated the phylogenetic structure patterns for species with different growth forms. We explored the relationships of these patterns with contemporary environment and historical climate change to test predictions of the tropical niche conservatism hypothesis (TCH) and to compare the contribution of different hypotheses using generalised linear models and hierarchical partitioning.We found that phylogenetic structure of angiosperms displayed significant latitudinal gradients. Notably, phylogenetic structure patterns and their drivers differed between woody and herbaceous species. Actual evapotranspiration was the best predictor of phylogenetic structure patterns for all and herbaceous species, while the mean temperature of the coldest quarter was the best predictor for woody species. The effect of historical climate change on phylogenetic structure patterns was weak.Our results suggest that the TCH only explains the phylogenetic structure pattern of woody species, not herbaceous species. Moreover, contemporary climate influences the phylogenetic structure of angiosperms in east Eurasian by affecting herbaceous and woody species differently. [ABSTRACT FROM AUTHOR]

Objective. The partial-volume effect (PVE) is an important factor impairing tumour quantification in molecular imaging. The commonly used contour-volume-of-interest (contour-VOI) approach to correct for this effect employs phantom-based recovery coefficients. Applying oversize-VOIs could offer superior quantification accuracy in small lesions. The oversize-VOI approach uses a large oversize volume to determine the total tumour activity after applying a background correction. Aims of this study were to provide a procedure for the application of the oversize-VOI approach and to compare its performance to the contour-VOI approach in PET imaging. Approach. A sphere tumour model was simulated to determine the oversize diameter that contained 90%, 95%, and 98% of the total activity as a function of the tumour size. Experimental investigations involving phantom and clinical data were conducted on a digital PET/CT scanner. In the phantom investigation, 12 spherical tumour inserts (diameters ranging from 3.7 to 37.4 mm) containing 18F-solution were used. The accuracy of the contour- and oversize-VOI approach was evaluated for different signal-to-background ratios (20–3). Clinically, both approaches were applied on PET/CT images acquired with 18F-labelled prostate-specific membrane antigen in prostate cancer patients. Main results. From the tumour model, we deduced that an oversize-VOI of two PET spatial resolutions larger than the physical lesion diameter contains at least 98% of the total activity for lesions with diameters down to one PET spatial resolution, while minimizing the background contribution. Both approaches were robust against varying phantom and clinical imaging conditions. Performance of the oversize-VOI approach was favorable for lesions below 10 mm in diameter, whereas the contour-VOI approach was slightly more accurate for sizes above 10 mm. Significance. The oversize-VOI approach facilitates image quantification of small tumours. It is simple and effective to correct for the PVE and may be used in pre-therapeutic (small) tumour dosimetry. [ABSTRACT FROM AUTHOR]

Recently, the use of unmanned aerial vehicles (UAVs) in bathymetric applications has become very popular due to the rapid and periodic acquisition of high spatial resolution data that provide detailed modeling of shallow water body depths and obtaining geospatial information. In UAV-based bathymetry, the sensor characteristics, imaging geometries, and the quality of radiometric and geometric calibrations of the imagery are the basic factors to achieve most reliable results. Digital bathymetric models (DBMs) that enable three-dimensional bottom topography definition of water bodies can be generated using many different techniques. In this paper, the effect of different UAV imaging bands and DBM generation techniques on the quality of bathymetric 3D modeling was deeply analyzed by visual and statistical model-based comparison approaches utilizing reference data acquired by a single-beam echosounder. In total, four different DBMs were generated and evaluated, two from dense point clouds derived from red--green--blue (RGB) single-band and multispectral (MS) fiveband aerial photos, and the other two from Stumpf and Lyzenga empirical satellite-based bathymetry (SDB) adapted to UAV data. The applications were performed in the Tavșan Island located in Istanbul, Turkey. The results of statistical model-based analyses demonstrated that the accuracies of the DBMs are arranged as RGB, MS, Lyzenga, and Stumpf from higher to lower and the standard deviation of height differences are between ±0.26 m and ±0.54 m. Visual results indicate that five-band MS DBM performs best in identifying the deepest areas. [ABSTRACT FROM AUTHOR]

The timing of spring onset is a particularly sensitive climate change indicator that also allows the study of weather interannual variations and extremes. This indicator can be derived from a suite of phenological models called the Extended Spring Indices (SI-x). These models transform daily minimum and maximum temperatures into a set of consistent indices that track the timing of first leaf and first bloom for key indicator plant species. The SI-x also enables the calculation of the so-called frost damage index. Using new computational technologies and high spatial resolution gridded weather data, here we present and evaluate a multi-decadal 1 km spatial resolution version of the SI-x models, which cover North American (1980 to 2022) and European areas (1950 to 2020). Because of the generally good agreement with ground phenological observations, this continental-scale and high spatial resolution product can support both scientists and decision makers in their quest to hind- and forecast weather and climate change impacts. [ABSTRACT FROM AUTHOR]

Holography is an ideal solution for truly 3D display. Complex‐amplitude hologram can realize high quality reconstructions compared to amplitude‐only hologram and phase‐only hologram. It is difficult for conventional spatial light modulators to achieve complex‐amplitude holographic display while ensuring temporal and spatial resolution, let alone color complex‐amplitude holographic display. Benefiting from the subwavelength pixel size and the powerful multi‐dimensional electromagnetic wave control capabilities, a few metasurface hologram with large viewing angle, high resolution, and no high‐order diffraction crosstalk based on complex‐amplitude control have been studied and realized. Nevertheless, colorful complex‐amplitude metasurface holography at visible frequency has not been implemented yet. Here a complex‐amplitude dual‐wavelength metasurface holography is proposed by using a single cross‐shaped meta‐atom. The polarization conversion efficiency of each wavelength channel is controlled by adjusting the geometric size, while the phase value from 0 to 2π is manipulated based on the Pancharatnam–Berry(PB) phase by rotating the meta‐atom. Without spatial multiplexing, the high‐resolution property of the metasurface is retained. The designed metasurface achieves dual‐color holographic display in the far‐field and the experimental results agree well with the simulation results. The proposed metasurface opens a pathway for high quality color holographic displays and other applications that require complex‐amplitude modulation at different wavelengths. [ABSTRACT FROM AUTHOR]

The inference of cell–cell communication (CCC) is crucial for a better understanding of complex cellular dynamics and regulatory mechanisms in biological systems. However, accurately inferring spatial CCCs at single-cell resolution remains a significant challenge. To address this issue, we present a versatile method, called DeepTalk, to infer spatial CCC at single-cell resolution by integrating single-cell RNA sequencing (scRNA-seq) data and spatial transcriptomics (ST) data. DeepTalk utilizes graph attention network (GAT) to integrate scRNA-seq and ST data, which enables accurate cell-type identification for single-cell ST data and deconvolution for spot-based ST data. Then, DeepTalk can capture the connections among cells at multiple levels using subgraph-based GAT, and further achieve spatially resolved CCC inference at single-cell resolution. DeepTalk achieves excellent performance in discovering meaningful spatial CCCs on multiple cross-platform datasets, which demonstrates its superior ability to dissect cellular behavior within intricate biological processes. cell–cell communication (CCC) is crucial for understanding biological processes. Here, authors present DeepTalk, which combines single-cell RNA sequencing and spatial transcriptomics data to infer cell–cell communication at single-cell resolution, revealing intricate intercellular dynamics within tissues. [ABSTRACT FROM AUTHOR]

In this study, we employ the Conformal Cubic Atmospheric Model (CCAM), a variable‐resolution global atmospheric model, driven by two distinct sea surface temperature (SST) data sets: the 0.25° Optimum Interpolation Sea Surface Temperature (CCAM_OISST) version 2.1 and the 2° Extended Reconstruction SSTs Version 5 (CCAM_ERSST5). Model performance is assessed using a benchmarking framework, revealing good agreement between both simulations and the climatological rainfall spatial pattern, seasonality, and annual trends obtained from the Australian Gridded Climate Data (AGCD). Notably, wet biases are identified in both simulations, with CCAM_OISST displaying a more pronounced bias. Furthermore, we have examined CCAM's ability to capture El Niño‐Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) correlations with rainfall during Austral spring (SON) utilizing a novel hit rate metric. Results indicate that only CCAM_OISST successfully replicates observed SON ENSO‐ and IOD‐rainfall correlations, achieving hit rates of 86.6% and 87.5%, respectively, compared to 52.7% and 41.8% for CCAM_ERSST5. Large SST differences are found surrounding the Australian coastline between OISST and ERSST5 (termed the "Coastal Effect"). Differences can be induced by the spatial interpolation error due to the discrepancy between model and driving SST. An additional CCAM experiment, employing OISST with SST masked by ERSST5 in 5° proximity to the Australian continent, underscores the "Coastal Effect" has a significant impact on IOD‐Australian rainfall simulations. In contrast, its influence on ENSO‐Australian rainfall is limited. Therefore, simulations of IOD‐Australian rainfall teleconnection are sensitive to local SST representation along coastlines, probably dependent on the spatial resolution of driving SST. Plain Language Summary: In this research, the Conformal Cubic Atmospheric Model (CCAM), a global atmospheric model, is used to study the impact of different driving sea surface temperature (SST) data sets on Australian rainfall simulations. Two SST data sets, one with high resolution (OISST) and another at lower resolution (ERSST5), are employed to drive CCAM (CCAM_OISST and CCAM_ERSST5). Model performance is evaluated using a benchmarking approach, indicating that both SST‐driven experiments are in good agreement with observed rainfall patterns in Australia. However, both simulations exhibit wet biases, with CCAM_OISST having a more noticeable bias. The study assesses CCAM's ability to capture the correlation between El Niño‐Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) with rainfall during Austral spring. Results reveal that CCAM_OISST performs better, replicating observed correlations more accurately than CCAM_ERSST5. The research identifies strong SST differences found between OISST and ERSST5 around the Australian coastline. An additional experiment underscores that this "Coastal Effect" plays an important role in simulating IOD‐Australian rainfall correlations, while its impact on ENSO‐Australian rainfall is limited. In conclusion, robust simulations of IOD‐Australian rainfall teleconnection require an accurate representation of local SST, which is related to the spatial resolution of SST products driving the model. Key Points: Novel hit rate metrics are proposed to evaluate El Niño‐Southern Oscillation and Indian Ocean Dipole‐rainfall teleconnectionsCCAM driven by different SST performs well in mean rainfall but ENSO and IOD related rainfall varies substantially over AustraliaResolution of the driving sea surface temperature is important to simulate IOD‐rainfall variability over Australia [ABSTRACT FROM AUTHOR]

Satellite remote sensing of aerosol is largely conducted at moderate or coarse spatial resolution around 1–10 km. Nevertheless, at urban areas with high human activity, aerosol can originate from complex emission sources and may also vary strongly in space. Therefore, aerosol characterization at fine spatial resolution is essential for air quality study and assessment of anthropogenic pollution as well as climate effects. However, space‐borne instruments with high spatial resolution are usually limited in swath width or spectral coverage which result in lowering information content required for aerosol and surface retrieval. Based on the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm, we propose a hybrid approach by combining fine and coarse spatial resolution measurements to retrieve aerosol and surface properties simulataneously at fine spatial resolution. The instruments with coarse spatial resolution and high revisting time can provide advanced aerosol characterization. At the same time, the instruments with fine spatial resolution are sensitive to spatial variability of aerosol nearby sources. In this study, the GRASP/Hybrid approach is demonstrated and tested based on the European Space Agency Sentinel‐5p/TROPOMI together with the Italian Space Agency PRISMA satellite data. Specifically, the detailed aerosol microphysical properties from Sentinel‐5p/TROPOMI 10 km retrievals are used as a priori information for PRISMA to derive aerosol loading and surface properties at 100 meter (m) spatial resolution. The PRISMA 100 m aerosol and surface retrieval based on the developed GRASP/Hybrid approach are evaluated using available ground‐based and satellite measurements, including AERONET, VIIRS/DB aerosol and PRISMA Level 2 surface reflectance products. Plain Language Summary: Both aerosol and surface characterization at high spatial resolution are always highly demanded especially over densely populated urban areas. However, the high spatial resolution space‐borne instruments typically have small swaths that, in general, reduce the possibility of aerosol and surface decoupling. In this paper, we develop a hybrid approach based on GRASP algorithm (GRASP/Hybrid) to retrieve aerosol and surface properties at fine spatial granularity by combining fine and coarse spatial resolution satellite data. The GRASP/Hybrid approach is demonstrated using European Space Agency (ESA) Sentinel‐5p/TROPOMI and Italian Space Agency (ASI) PRISMA (Hyperspectral Precursor of the Application Mission) measurements. Specifically, the detailed aerosol microphysical properties from Sentinel‐5p/TROPOMI 10 km retrievals are used as a priori information to derive aerosol loading and surface properties exploiting PRISMA at 100 m spatial resolution. Overall, the results obtained in this study demonstrate the big potential of the approach based on the combination of instruments for a number of climate and environment monitoring studies. Key Points: Generalized Retrieval of Atmosphere and Surface Properties (GRASP)/Hybrid approach is developed and demonstrated using Sentinel‐5p/TROPOMI and PRISMA measurementsPRISMA 100 m aerosol and surface properties are retrieved based on GRASP/Hybrid approach and evaluated using reference data setsWe demonstrate the big potential of hybrid approach based on the combination of instruments for climate and environment studies [ABSTRACT FROM AUTHOR]

The Multisensor Multiresolution Technique (MMT) is applied to unmixed thermal images from ASTER (90 m), using 30 m resolution images from Landsat 8-9 reflective channels. The technique allows for the retrieval of thermal radiance values of the features identified in the high-resolution reflective images and the generation of a high-resolution radiance image. Different alternatives of application of MMT are evaluated in order to determine the optimal methodology design: performance of the Iterative Self-Organizing Data Analysis Technique (ISODATA) and K-means classification algorithms, with different initiation numbers of clusters, and computation of contributions of each cluster using moving windows with different sizes and with and without weight coefficients. Results show the K-means classification algorithm with five clusters, without matrix weighting, and utilizing a 5 × 5 pixel window for synthetic high-resolution image reconstruction. This approach obtained a maximum R2 of 0.846 and an average R2 of 0.815 across all cases, calculated through the validation of the synthetic high-resolution TIR image generated against a real Landsat 8-9 TIR image from the same area, same date, and co-registered. These values imply a 0.89% improvement regarding the second-best methodology design (K-means with five starting clusters with 7 × 7 moving window) and a 410.25% improvement regarding the worst alternative (K-means with nine initial clusters, weighting, and 3 × 3 moving window). [ABSTRACT FROM AUTHOR]

Emotional distractors capture spatial attention delaying target search more than neutral distractors. The current study investigated whether emotional attention capture occurs automatically by utilizing statistical learning to suppress attention capture. Participants searched for a target while an emotional or neutral distractor appeared at high (suppressed) or low distractor probability (not suppressed) locations. Experiment 1 (56 subjects) measured target detection latency with a keyboard and Experiment 2 (90 subjects) used computer mouse tracking for measuring emotional capture at higher spatial and temporal resolutions. Results showed that emotional capture of spatial attention was able to be suppressed, but at the cost of producing non-spatial time delays. Furthermore, emotional capture that occurred at non-suppressed locations occurred at relatively late temporal stages after movement initiation and were more likely to occur in individuals with high trait anxiety. Overall, the study demonstrates that emotional capture of spatial attention is not strictly automatic. [ABSTRACT FROM AUTHOR]

Molecular scaffolds are ideal for investigating upconversion (UC) at the highest spatial resolution and to create precisely controllable luminescent materials. Such control may be the key to overcoming the limitations of brightness and reproducibility found in UC micro‐ and nanoparticles. Cooperative UC can significantly increase luminescence brightness and bulk studies showed that highest efficiencies can be obtained by sensitizer‐to‐activator ion ratios ≥ 2, that is, via high probabilities of sensitizing the emitting lanthanide ion. Using nonanuclear molecular complexes, the authors demonstrate both experimentally and theoretically that interion distances are more relevant and that the highest UC efficiencies are actually attained for sensitizer‐to‐activator ion ratios around 1. By modeling accretive and cooperative sensitization UC, energy migration, and fitting experimental data, it is revealed that cooperative sensitization is predominant for the determination of UC luminescence intensities, whereas energy migration defines UC luminescence kinetics. The implementation of interion distances and different energy transfer mechanisms into advanced modeling of experimental UC data will be paramount for designing brighter and better UC materials. [ABSTRACT FROM AUTHOR]