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Previous work suggests that synergistic activity among motor elements implicated in force production tasks underlies enhanced performance stability associated with visual feedback. A hallmark of synergistic activity is reciprocal compensation, that is, covariation in the states of motor elements that stabilizes critical performance variables. The present study examined if characteristics of reciprocal compensation are indicators of individuals' capacity to respond adaptively to variations in the resolution of visual feedback about criterion performance. Twenty healthy adults (19.25 ± 1.25 years; 15 females and five males) pressed two sensors with their index fingers to produce a total target force equivalent to 20% of their maximal voluntary contraction under nine conditions that differed in the spatial resolution of real-time feedback about their performance. By combining within-trial uncontrolled manifold and sample entropy analyses, we quantified the amount and degree of irregularity (i.e., non-repetitiveness) of reciprocal compensations over time. We found a U-shaped relationship between performance stability and gain. Importantly, this relationship was moderated by the degree of irregularity of reciprocal compensation. Lower irregularity in reciprocal compensation patterns was related to individuals' capacity to maintain (or minimize losses in) performance under changes in feedback resolution. Results invite future investigation into how interindividual variations in reciprocal compensation patterns relate to differences in control strategies supporting adaptive responses in complex, visually guided motor tasks. [ABSTRACT FROM AUTHOR]

A recent ground-breaking experimental study [Lyons et al., Phys. Rev. X 14(1), 011017 (2024)] reports on measuring the temporal duration and the spatial extent of failed attempts to cross an activation barrier (i.e., "loops") for a folding transition in a single molecule and for a Brownian particle trapped within a bistable potential. Within the model of diffusive dynamics, however, both of these quantities are, on average, exactly zero because of the recrossings of the barrier region boundary. That is, an observer endowed with infinite spatial and temporal resolution would find that finite loops do not exist (or, more precisely, form a set of measure zero). Here we develop a description of the experiment that takes the "fuzziness" of the boundaries caused by finite experimental resolution into account and show how the experimental uncertainty of localizing the point, in time and space, where the barrier is crossed leads to observable distributions of loop times and sizes. Although these distributions generally depend on the experimental resolution, this dependence, in certain cases, may amount to a simple resolution-dependent factor and, therefore, the experiments do probe inherent properties of barrier crossing dynamics. [ABSTRACT FROM AUTHOR]

Surface functionalization of low-dimensional nanomaterials offers a means to tailor their optoelectronic and chemical characteristics. However, functionalization reactions are sensitive to the inherent surface features of nanomaterials, such as defects, grain boundaries, and edges. Conventional optical characterization methods, such as Raman spectroscopy, have limited sensitivity and spatial resolution and, therefore, struggle to visualize reaction sites and chemical species. Here, we demonstrate the capability of spatially and chemically sensitive tip-enhanced Raman spectroscopy imaging to map the distribution of molecules in covalently functionalized graphene. Hyperspectral vertex component analysis and density functional theory are necessary to interpret the nature of binding sites and extract information from the spatially and spectrally heterogeneous datasets. Our results clarify the origin of heterogeneous surface functionalization, resolving preferential binding at edges and defects. This work demonstrates the potential of nanospectroscopic tools combined with unsupervised learning to characterize complex, partially ordered optoelectronic nanomaterials. [ABSTRACT FROM AUTHOR]

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]

High transparency Ce3+-doped dense gadolinium aluminum borosilicate (GS x) glass scintillator was synthesized in reducing atmosphere by melt-quenching process. The transmittance of the glasses exceeds 80%, and the light attenuation length is between 5-20 cm within the range of 400–600 nm. GS x glass shows an photoluminescence (PL) in range of 350–550 nm, with the strongest emission peak around 420 nm. The PL decay time of GS x glasses is around 37 ns, with a maximum PL quantum yield of 44.05%. The integrated X-ray excited luminescence (XEL) intensity of GS S glass is 52.5% compared with BGO crystal. For X-ray imaging, GS L glass based imaging system shows a high spatial resolution of 9 lp/mm, which is comparable to CsI:Tl X-ray detectors. Under γ-ray, the highest light yield of GS S glass is 1235 ph/MeV with an energy resolution of 24.0% at 662 keV, close to that of BSO crystal. The scintillation decay time of GS x glasses is consisted of fast (∼100 ns) and slow (∼560 ns) components. In thermally stimulated luminescence (TSL), GS S glass exhibits a strong TSL peak at approximately 440 K, with low intensity shoulders at about 520 K, implying different types of defects and traps. Therefore, GS x glass has promising prospects for X-ray imaging and high-energy physics applications. [ABSTRACT FROM AUTHOR]

The preparation of histology slides is a critical step in histopathology, and poor-quality histology slides with weak adhesion of tissue sections to the substrate often affect diagnostic accuracy and sometimes lead to diagnostic failure due to tissue section detachment. This issue has been of concern and some methods have been proposed to enhance tissue-substrate adhesion. Unfortunately, quantitative analysis of the adhesion between tissue sections and glass slides is still challenging. In this work, the adhesion of mouse brain tissue sections on gold-coated glass slides was analyzed using a laboratory-fabricated hyperspectral surface plasmon resonance microscopy (HSPRM) system that enabled single-pixel spectral SPR sensing and provided two-dimensional (2D) distribution of resonance wavelengths (RWs). The existence of the nanoscale water gap between the tissue section and the substrate was verified by fitting the RW measured in each pixel using the five-layer Fresnel reflection model. In addition, a 2D image of the tissue-substrate adhesion distance (AD) was obtained from the measured 2D distribution of RWs. The results showed that tissue-substrate AD was 20–35 nm in deionized water and 4–24 nm in saline solution. The HSPRM system used in this work has a wide wavelength range of 400–1000 nm and can perform highly sensitive and label-free detection over a large dynamic detection range with high spectral and spatial resolutions, showing significant potential applications in stain-free tissue imaging, quantitative analysis of tissue-substrate adhesion, accurate identification of tumor cells, and rapid histopathological diagnosis. [ABSTRACT FROM AUTHOR]

Image enhancement is the process of improving the quality of a digital image. Improved image quality is one of the goals of the ongoing effort to improve the information content and interpretability of satellite images. Two sets of remote sensing data were collected for this region: one from the SPOT-4 (2018) satellite and the other from the Enhanced Thematic Mapper Plus (ETM+) Landsat 7 (2020) satellite. This study used two images taken at various spatial resolutions of the same location. Two images are shown here: one with a 30 m spatial resolution and the other with a 5 m resolution with multispectral processing. The results indicate that integrating spatial and spectral resolution using geomatics techniques significantly benefits various applications. Before merging the images, it was root mean square error (RMSE) 11.55 Easting, 5.77 Northing and became 1.52 Easting, 1.45 Northing after merging the images. After implementing the approach, the resulting fusing image exhibits enhanced spatial resolution, and the resulting multispectral image has excellent spatial as well as spectral resolution. Finally, the improved combined image with great spatial and spectral resolution is prepared for analysis and classification. [ABSTRACT FROM AUTHOR]

The cerebral cortex comprises many distinct regions that differ in structure, function, and patterns of connectivity. Current approaches to parcellating these regions often take advantage of functional neuroimaging approaches that can identify regions involved in a particular process with reasonable spatial resolution. However, neuroanatomical biomarkers are also very useful in identifying distinct cortical regions either in addition to, or in place of functional measures. For example, differences in myelin density are thought to relate to functional differences between regions, are sensitive to individual patterns of experience, and have been shown to vary across functional hierarchies in a predictable manner. Accordingly, the current study provides quantitative stereological estimates of myelin density for each of the 13 regions that make up the feline auditory cortex. We demonstrate that significant differences can be observed between auditory cortical regions, with the highest myelin density observed in the regions that comprise the auditory core (i.e., the primary auditory cortex and anterior auditory field). Moreover, our myeloarchitectonic map suggests that myelin density varies in a hierarchical fashion that conforms to the traditional model of spatial organization in auditory cortex. Taken together, these results establish myelin as a useful biomarker for parcellating auditory cortical regions, and provide detailed estimates against which other, less invasive methods of quantifying cortical myelination may be compared. [ABSTRACT FROM AUTHOR]

Based on the conventional beamforming (CBF), some algorithms for far-field sound source identification have been proposed in the past few decades. Typically, the functional beamforming (FBF) and the deconvolution methods, such as CLEAN, CLEAN with source coherence (CLEAN-SC), CLEAN-SC with compressed grids (CLEAN-SC-CG), CLEAN with cross spectral matrix function (CLEAN-CSM), High-resolution CLEAN-SC (HR-CLEAN-SC), are frequently mentioned and their advantages are widely discussed in the previous literatures. To assess their efficacy and suitability in engineering applications, with a focus on spatial resolution, computational efficiency, and dynamic range, a comparative study by locating two types of sound sources is carried out. The first scenario represents the case where the distance between two sound sources is smaller than the Rayleigh limit, while the second scenario represents the situation involving multiple sound sources, such as four or more complex sound sources. The analysis demonstrates that CBF, CLEAN, and CLEAN-SC cannot surpass the Rayleigh limit. However, FBF, CLEAN-SC-CG, CLEAN-CSM, and HR-CLEAN-SC have the potential to overcome it. In FBF, the grid mismatch results in a compromise between its dynamic range and source strength estimation. Meanwhile, HR-CLEAN-SC requires prior knowledge of the number of sound sources, which is challenging in applications. Because of superiority in the fundamental acoustic image and searching strategy, CLEAN-CSM and CLEAN-SC-CG exhibits superior features compared to the others. By compressing the number of grids, the CLEAN-SC-CG can improve the computational efficiency up to at least 46%. By constructing the cross spectral matrix function related to the real source, CLEAN-CSM uses the power function to simultaneously enhance the spatial resolution, dynamic range and source strength estimation. The conclusions are further validated through sound-source identification experiments involving two loudspeakers and an engine. The findings presented in this paper serve to guide the selection of suitable approaches for multi-sound source identification in engineering applications. [ABSTRACT FROM AUTHOR]

Crater identification aims to match the craters of a planetary body observed in an image to the corresponding entries in a catalogue of known craters of the same body. It is a key step in crater-based navigation algorithms for planetary missions. Many crater identification methods extract descriptors from the observed craters and compare them to an index of descriptors constructed a priori from the crater catalogue. The need for viewpoint invariance motivates descriptors defined over crater tuples (e.g. , crater triads for projective invariance). However, this implies a descriptor index that grows rapidly (e.g. , cubically) with the size of the catalogue, which practically limits the spatial resolution and/or coverage of the catalogue. Another serious drawback is the sensitivity of the descriptors and the matching accuracy to noise and outliers in the crater detection result, which are inevitable due to imperfect crater detection algorithms. In this paper, we propose a novel descriptorless crater identification technique. At its core, our method solves the perspective cone alignment problem with geometric verification iteratively over the crater catalogue. We show that our simple algorithm, with time and space complexities that are linear in the catalogue size, is substantially more accurate than state-of-the-art descriptor-based methods in the presence of noise. Moreover, the availability of multi-core onboard processors raises the prospect of speeding up our method through parallelisation. • This paper introduces the first descriptor-less crater identification method. • It comprises a perspective cone alignment solver and a geometric verification scheme. • It achieves 2–3 orders of magnitude memory improvement over descriptor-based methods. • It demonstrated superior robustness against input noise and challenging conditions. [ABSTRACT FROM AUTHOR]

Approximately 70%–75% of people worldwide have no formally registered land rights. Fit-For-Purpose Land Administration was introduced to address this problem and focuses on delineating visible cadastral boundaries from earth observation imagery. Recent studies have shown the potential of deep learning models to extract these visible cadastral boundaries automatically. However, studies are limited by the small size and geographical coverage of available datasets and by the lack of information about which cadastral boundaries are visible, i.e., associated with a physical object boundary. To overcome these problems, we present CadastreVision , a benchmark dataset containing cadastral reference data and corresponding multi-resolution earth observation imagery from The Netherlands, with a spatial resolution ranging from 0.1 m to 10 m. The ratio between visible and non-visible cadastral boundaries is essential to evaluate the potential automation level in cadastral boundary extraction from earth observation images and interpret results obtained by deep learning models. We investigate this ratio using a novel analysis pipeline that overlays cadastral reference data with visible topographic object boundaries. Our results show that approximately 72% of the total length of cadastral boundaries in The Netherlands are visible. CadastreVision will enable new developments in cadastral boundary delineation and future endeavours to investigate knowledge transfer to data-scarce areas. Our data and code is available at https://github.com/jeroengrift/cadastrevision. [Display omitted] [ABSTRACT FROM AUTHOR]

Purpose: Quantitative T1 mapping has the potential to replace biopsy for noninvasive diagnosis and quantitative staging of chronic liver disease. Conventional T1 mapping methods are confounded by fat and B1+$$ {B}_1^{+} $$ inhomogeneities, resulting in unreliable T1 estimations. Furthermore, these methods trade off spatial resolution and volumetric coverage for shorter acquisitions with only a few images obtained within a breath‐hold. This work proposes a novel, volumetric (3D), free‐breathing T1 mapping method to account for multiple confounding factors in a single acquisition. Theory and Methods: Free‐breathing, confounder‐corrected T1 mapping was achieved through the combination of non‐Cartesian imaging, magnetization preparation, chemical shift encoding, and a variable flip angle acquisition. A subspace‐constrained, locally low‐rank image reconstruction algorithm was employed for image reconstruction. The accuracy of the proposed method was evaluated through numerical simulations and phantom experiments with a T1/proton density fat fraction phantom at 3.0 T. Further, the feasibility of the proposed method was investigated through contrast‐enhanced imaging in healthy volunteers, also at 3.0 T. Results: The method showed excellent agreement with reference measurements in phantoms across a wide range of T1 values (200 to 1000 ms, slope = 0.998 (95% confidence interval (CI) [0.963 to 1.035]), intercept = 27.1 ms (95% CI [0.4 54.6]), r2 = 0.996), and a high level of repeatability. In vivo imaging studies demonstrated moderate agreement (slope = 1.099 (95% CI [1.067 to 1.132]), intercept = −96.3 ms (95% CI [−82.1 to −110.5]), r2 = 0.981) compared to saturation recovery‐based T1 maps. Conclusion: The proposed method produces whole‐liver, confounder‐corrected T1 maps through simultaneous estimation of T1, proton density fat fraction, and B1+$$ {B}_1^{+} $$ in a single, free‐breathing acquisition and has excellent agreement with reference measurements in phantoms. [ABSTRACT FROM AUTHOR]

Purpose: To develop and demonstrate a fast 3D fMRI acquisition technique with high spatial resolution over a reduced FOV, named k‐t 3D reduced FOV imaging (3D‐rFOVI). Methods: Based on 3D gradient‐echo EPI, k‐t 3D‐rFOVI used a 2D RF pulse to reduce the FOV in the in‐plane phase‐encoding direction, boosting spatial resolution without increasing echo train length. For image acceleration, full sampling was applied in the central k‐space region along the through‐slab direction (kz) for all time frames, while randomized undersampling was used in outer kz regions at different time frames. Images were acquired at 3T and reconstructed using a method based on partial separability. fMRI detection sensitivity of k‐t 3D‐rFOVI was quantitively analyzed with simulation data. Human visual fMRI experiments were performed to evaluate k‐t 3D‐rFOVI and compare it with a commercial multiband EPI sequence. Results: The simulation data showed that k‐t 3D‐rFOVI can detect 100% of fMRI activations with an acceleration factor (R) of 2 and ˜80% with R = 6. In the human fMRI data acquired with 1.5‐mm spatial resolution and 800‐ms volume TR (TRvol), k‐t 3D‐rFOVI with R = 4 detected 46% more activated voxels in the visual cortex than the multiband EPI. Additional fMRI experiments showed that k‐t 3D‐rFOVI can achieve TRvol of 480 ms with R = 6, while reliably detecting visual activation. Conclusions: k‐t 3D‐rFOVI can simultaneously achieve a high spatial resolution (1.5‐mm isotropically) and short TRvol (480‐ms) at 3T. It offers a robust acquisition technique for fast fMRI studies over a focused brain volume. [ABSTRACT FROM AUTHOR]

In 1998, the South Carolina Geological Survey (SCGS) established a state-wide coastal Surface Elevation Table (SET) network to document geodetic elevation changes (uplift or subsidence) at different spatial resolutions, quantify elevation change on salt marsh platforms over time, and compare the rate of surface elevation change (REC) at each station to the rate of local relative sea-level rise (RSLR). Analysis of short- and long-term (4 to 22 + year) datasets from 21 SCGS SET stations shows that rates vary widely, from -2.30 to + 10.17 mm/yr. The 22 + year length of record on the oldest SCGS SET datasets reveal non-linear REC trends, with short-term trends often above or below the long-term trendline. When compared to a 100-year RSLR trend of 3.36 ± 0.19 mm/year at NOAA gauge 8,665,530 (Cooper River Mouth, Charleston Harbor), 11 stations had higher rates, five were lower, and five had overlapping confidence intervals. With a shorter 23-year record, only two stations would have higher rates. All SCGS SET stations are situated high in the tidal frame. There are no discernible associations between SET positions relative to mean high water (MHW) and REC. Long-term (1998–2021) geodetic elevation data available for six of the original stations indicate some geodetic elevation loss. Data for these original stations, and nine upland benchmarks surveyed in 2022, indicate possible impacts from the underlying Garner-Edisto fault. These findings have implications for other SET programs using similar methods to quantify vertical change over decadal time spans. [ABSTRACT FROM AUTHOR]

Previously, we developed an "activity painting" tool for PET image simulation; however, it could simulate heterogeneous patterns only in the air. We aimed to improve this phantom technique to simulate arbitrary lesions in a radioactive background to perform relevant multi-center radiomic analysis. We conducted measurements moving a 22Na point source in a 20-liter background volume filled with 5 kBq/mL activity with an adequately controlled robotic system to prevent the surge of the water. Three different lesion patterns were "activity-painted" in five PET/CT cameras, resulting in 8 different reconstructions. We calculated 46 radiomic indeces (RI) for each lesion and imaging setting, applying absolute and relative discretization. Reproducibility and reliability were determined by the inter-setting coefficient of variation (CV) and the intraclass correlation coefficient (ICC). Hypothesis tests were used to compare RI between lesions. By simulating precisely the same lesions, we confirmed that the reconstructed voxel size and the spatial resolution of different PET cameras were critical for higher order RI. Considering conventional RIs, the SUVpeak and SUVmean proved the most reliable (CV<10%). CVs above 25% are more common for higher order RIs, but we also found that low CVs do not necessarily imply robust parameters but often rather insensitive RIs. Based on the hypothesis test, most RIs could clearly distinguish between the various lesions using absolute resampling. ICC analysis also revealed that most RIs were more reproducible with absolute discretization. The activity painting method in a real radioactive environment proved suitable for precisely detecting the radiomic differences derived from the different camera settings and texture characteristics. We also found that inter-setting CV is not an appropriate metric for analyzing RI parameters' reliability and robustness. Although multicentric cohorts are increasingly common in radiomics analysis, realistic texture phantoms can provide indispensable information on the sensitivity of an RI and how an individual RI parameter measures the texture. [ABSTRACT FROM AUTHOR]

Background: Spatial proteomics seeks to understand the spatial organization of proteins in tissues or at different subcellular localization in their native environment. However, capturing the spatial organization of proteins is challenging. Here, we present an innovative approach termed Spatial Proteomics through On-site Tissue-protein-labeling (SPOT), which combines the direct labeling of tissue proteins in situ on a slide and quantitative mass spectrometry for the profiling of spatially-resolved proteomics. Materials and Methods: Efficacy of direct TMT labeling was investigated using seven types of sagittal mouse brain slides, including frozen tissues without staining, formalin-fixed paraffin-embedded (FFPE) tissues without staining, deparaffinized FFPE tissues, deparaffinized and decrosslinked FFPE tissues, and tissues with hematoxylin & eosin (H&E) staining, hematoxylin (H) staining, eosin (E) staining. The ability of SPOT to profile proteomes at a spatial resolution was further evaluated on a horizontal mouse brain slide with direct TMT labeling at eight different mouse brain regions. Finally, SPOT was applied to human prostate cancer tissues as well as a tissue microarray (TMA), where TMT tags were meticulously applied to confined regions based on the pathological annotations. After on-site direct tissue-protein-labeling, tissues were scraped off the slides and subject to standard TMT-based quantitative proteomics analysis. Results: Tissue proteins on different types of mouse brain slides could be directly labeled with TMT tags. Moreover, the versatility of our direct-labeling approach extended to discerning specific mouse brain regions based on quantitative outcomes. The SPOT was further applied on both frozen tissues on slides and FFPE tissues on TMAs from prostate cancer tissues, where a distinct proteomic profile was observed among the regions with different Gleason scores. Conclusions: SPOT is a robust and versatile technique that allows comprehensive profiling of spatially-resolved proteomics across diverse types of tissue slides to advance our understanding of intricate molecular landscapes. [ABSTRACT FROM AUTHOR]

Metal–organic frameworks (MOFs) have emerged as a versatile class of materials. Understanding the structural and chemical properties of MOFs is essential for tailoring their performance to suit specific applications. In recent years, Raman spectroscopy, a non‐destructive vibrational spectroscopic technique, has evolved into a powerful tool for characterizing MOFs. Beyond spontaneous Raman scattering, numerous advanced Raman techniques have been developed to amplify the inherently weak Raman signal. These innovations have significantly enhanced the spatial resolution, frame rate, and sensitivity of Raman imaging, thereby opening up new possibilities for applications, such as label‐free sensing. This tutorial work is designed to demystify the fundamental theory and instrumentation of Raman spectroscopy, elucidating the differences between commonly used Raman techniques. Particular emphasis is placed on their advantages and limitations when applied to MOF materials. Furthermore, this work showcases how Raman techniques are employed in studying MOF systems to address societal needs and explore future directions. Ultimately, this review emphasizes the crucial role of Raman spectroscopy and the development of novel Raman‐based in situ techniques to conquer the field of MOFs. [ABSTRACT FROM AUTHOR]

The utilization of satellite images in conservation research is becoming more prevalent due to advancements in remote sensing technologies. To achieve accurate classification of wildlife habitats, it is important to consider the different capabilities of spectral and spatial resolution. Our study aimed to develop a method for accurately classifying habitat types of the Himalayan ibex (Capra sibirica) using satellite data. We used LISS IV and Sentinel 2A data to address both spectral and spatial issues. Furthermore, we integrated the LISS IV data with the Sentinel 2A data, considering their individual geometric information. The Random Forest approach outperformed other algorithms in supervised classification techniques. The integrated image had the highest level of accuracy, with an overall accuracy of 86.17% and a Kappa coefficient of 0.84. Furthermore, to delineate the suitable habitat for the Himalayan ibex, we employed ensemble modelling techniques that incorporated Land Cover Land Use data from LISS IV, Sentinel 2A, and Integrated image, separately. Additionally, we incorporated other predictors including topographical features, soil and water radiometric indices. The integrated image demonstrated superior accuracy in predicting the suitable habitat for the species. The identification of suitable habitats was found to be contingent upon the consideration of two key factors: the Soil Adjusted Vegetation Index and elevation. The study findings are important for advancing conservation measures. Using accurate classification methods helps identify important landscape components. This study offers a novel and important approach to conservation planning by accurately categorising Land Cover Land Use and identifying critical habitats for the species. [ABSTRACT FROM AUTHOR]

ABSTRACT This study monitored 37 longliners fishing in waters near the Marshall Islands from 2020 to 2022 by Liancheng Overseas Fishery (Shenzhen) Co., Ltd.'s operation management system. This study developed nine predictive models on the relationship between catch per unit effort (CPUE) data for yellowfin tuna (Thunnus albacares) and the environmental data. The environmental data integrate 48 variables, including eddy kinetic energy, chlorophyll a concentration, sea surface height, and additional measures of vertical oceanic conditions, alongside spatiotemporal parameters (year, month, day, longitude, and latitude). This study employed four spatial resolutions (0.25° × 0.25°, 0.5° × 0.5°, 1° × 1°, and 2° × 2°) to develop nine predictive models: KNN, RF, GBDT, CART, LightGBM, XGBoost, CatBoost, AdaBoost, and Stacking (RF, KNN, GBDT, and LR). These models, with a daily time resolution, were trained using 75% of the data and tested with the remaining 25%. The optimal spatial resolution and model were determined through a comprehensive comparison of model evaluation metrics across these spatial resolutions. The SMOTETomek algorithm was then applied to resample 75% of the data at the optimal spatial resolution, forming a new training dataset. This dataset was used to refine the model, subsequently tested with the remaining 25% of the data. Results indicated that (1) the optimal spatial resolution is 0.25° × 0.25° and the optimal model is RF; (2) the SMOTETomek algorithm enhances the model's predictive performance; and (3) the developed SMK‐RF model, exhibiting Acc and AUC values of 76.73% and 82.47%, respectively, accurately predicts the central fishing grounds for yellowfin tuna, consisting closely with actual fishing activity. [ABSTRACT FROM AUTHOR]

Copper‐based organic–inorganic hybrid halides (OIHHs) have garnered significant interest in X‐ray imaging due to their flexible structural adjustability, efficient light emission, strong X‐ray absorption, etc. Herein, four copper‐based OIHH crystals composed of the same organic ligands (isopropyl triphenylphosphonium cations, IPP+) and inorganic parts (Cu2I42−) are synthesized by varying the ratios of raw materials and types of reaction solvents. Although these crystals share identical structures, they exhibit different luminescent behaviors (blue, green, white, and yellow) attributed to vacancy defects originating from CuI. Notably, the novel copper‐based OIHH (CP2) with green emission shows the best luminescence efficiency (99.54%) and excellent scintillation performance (50675 photons MeV−1). The traditional technology of scintillation screens mixing scintillator powders and polymers often results in light scattering due to powder aggregation and inhomogeneity. To address this challenge, the dispersant polyvinyl pyrrolidone is introduced to prepare uniform rod‐like microcrystals of CP2. The scintillation screen based on CP2 microcrystals achieves a high spatial resolution of 16–18 lp mm−1, surpassing the resolution of most copper‐based OIHH scintillators. Furthermore, it is imaging capabilities are validated using a commercial X‐ray flat panel detector, demonstrating imaging performance comparable to that of commercial scintillators. [ABSTRACT FROM AUTHOR]

Background Purpose Methods Results Conclusions Long‐axis positron emission tomography (PET) has emerged as one of the recent research directions in PET due to its ability to significantly enhance sensitivity and counting performance for low‐dose imaging, rapid imaging, and whole‐body dynamic imaging.The PET system presented in this study is a long‐axis animal PET based on lutetium–yttrium orthosilicate and silicon photomultiplier, designed for whole‐body imaging in rats. It features a diameter of 143 mm and an axial length of 213.3 mm. This study evaluated the performance of this PET system in accordance with the National Electrical Manufacturers Association (NEMA) NU 4‐2008 standards.The performance evaluation was conducted according to the NEMA NU 4‐2008 standards in terms of spatial resolution, sensitivity, counting rate performance, scatter fraction (SF) and image quality. In addition, a rat imaging study was conducted to assess the imaging capability of this PET system.The average energy resolution of the PET system was 12.87%, the average coincidence timing resolution was 751 ps. The FWHM of spatial resolution reconstructed by filtered back projection and 3D‐OSEM‐PSF algorithm at 5 mm radial offset from the axial center were 1.65 and 0.88 mm. The peak absolute sensitivity measured by a point source at the center of the field of view was evaluated as 6.71% (361–661 keV) and 10.31% (250–750 keV). For the mouse‐like phantom, the SF was 11.0% and the peak noise equivalent counting rate (NECR) was 1193 kcps at 94.2 MBq (2.54 mCi). For the rat‐like phantom, the SF was 26.8% and the NECR was 682.5 kcps at 78.6 MBq (2.12 mCi).The performance measurement results demonstrate that this PET system exhibits high sensitivity and count rate performance, making it potential for high‐quality whole‐body dynamic imaging of rats. [ABSTRACT FROM AUTHOR]

Purpose Methods Results Conclusion The performance of detectors is key for a PET scanner to achieve high spatial resolution and high sensitivity. This work aims to develop flood histogram generating algorithms to reduce the edge effect and improve the crystal identification of a PET detector consisting of two optically coupled pixelated scintillator detectors.The PET detector consists of two optically coupled detectors, each consisting of a 23×23 LYSO crystal array with a crystal size of 1.0×1.0×20 mm3 read out by an 8×8 SiPM array with a pixel size of 3.0×3.0 mm2. The SiPM array is read out with a resistor network circuit to obtain four position encoding energy signals. A novel center of gravity (COG) positioning algorithm using six signals from the two detectors was proposed and compared to the traditional COG algorithms using either four or eight signals from the detectors. The raised‐to‐the‐power (RTP) method was applied to the three COG algorithms for the PET detector. Different powers of the RTP from 1.0 to 2.5 were evaluated.The proposed COG algorithm significantly improves the crystal identification at the junction of the two detectors as compared to the COG algorithm using four signals of each detector, and improves the crystal identification at the center of the two detectors as compared to the COG algorithm using eight signals from both detectors. The RTP method significantly improves the overall flood histogram qualities of the two COG algorithms using either eight or six signals from the two detectors, and the two COG algorithm provide similar flood histogram quality when a power of 1.5 is used.The novel positioning algorithms reduce the edge effect and improve the flood histogram quality for a PET detector consisting of two optically coupled detectors, each consisting of a pixelated scintillator crystal array and a SiPM array with highly multiplexed four signal readout. The positioning algorithms can be used in a PET scanner to improve the spatial resolution and sensitivity. [ABSTRACT FROM AUTHOR]

Materials and their interfaces are the core for the development of a large variety of fields, including catalysis, energy storage and conversion. In this case, tip-enhanced Raman spectroscopy (TERS), which combines scanning probe microscopy with plasmon-enhanced Raman spectroscopy, is a powerful technique that can simultaneously obtain the morphological information and chemical fingerprint of target samples at nanometer spatial resolution. It is an ideal tool for the nanoscale chemical characterization of materials and interfaces, correlating their structures with chemical performances. In this review, we begin with a brief introduction to the nanoscale characterization of materials and interfaces, followed by a detailed discussion on the recent theoretical understanding and technical improvements of TERS, including the origin of enhancement, TERS instruments, TERS tips and the application of algorithms in TERS. Subsequently, we list the key experimental issues that need to be addressed to conduct successful TERS measurements. Next, we focus on the recent progress of TERS in the study of various materials, especially the novel low-dimensional materials, and the progresses of TERS in studying different interfaces, including both solid–gas and solid–liquid interfaces. Finally, we provide an outlook on the future developments of TERS in the study of materials and interfaces. [ABSTRACT FROM AUTHOR]

Introduction: Event-Related Potentials (ERPs) are valuable for studying brain activity withmillisecond-level temporal resolution. While the temporal resolution of this technique is excellent, the spatial resolution is limited. Source localization aims to identify the brain regions generating the EEG data, thus increasing the spatial resolution, but its accuracy depends heavily on the headmodel used. This study compares the performance of subject-specific and template-based head models in both simulated and real-world ERP localization tasks. Methods: Simulated data mimicking realistic ERPs was created to evaluate the impact of head model choice systematically, after which subject-specific and template-based head models were used for the reconstruction of the data. The different modeling approaches were also applied to a face recognition dataset. Results: The results indicate that the template models capture the simulated activity less accurately, producing more spurious sources and identifying less true sources correctly. Furthermore, the results show that while creating more accurate and detailed head models is beneficial for the localization accuracy when using subject-specific head models, this is less the case for template head models. The main N170 source of the face recognition dataset was correctly localized to the fusiformgyrus, a known face processing area, using the subject-specificmodels. Apart fromthe fusiformgyrus, the templatemodels also reconstructed several other sources, illustrating the localization inaccuracies. Discussion: While template models allow researchers to investigate the neural generators of ERP components when no subject-specific MRIs are available, it could lead to misinterpretations. Therefore, it is important to consider a priori knowledge and hypotheses when interpreting results obtained with template head models, acknowledging potential localization errors. [ABSTRACT FROM AUTHOR]

Light field (LF) image super-resolution (SR) is a technique designed to enhance the details and clarity of low-resolution (LR) light field images by leveraging the additional information and structure present within the LF data. With the rise of deep learning, the performance of LF image super-resolution has been significantly improved, but it has led to an increase in model parameters and computational complexity, resulting in a phenomenon of excessive reliance on computational resources. To address this problem, this paper proposes a lightweight but effective model. In our approach, we employ Swin Attention to extract features from LF images. Window and Shifted Window are the main components of Swin Attention. Therefore, the local features of the LF images are captured using Window, and feature correlations are established through Shifted Window. Furthermore, we introduce Extensive Attention (EA) blocks to capture the global features of the LF image. In addition to the aforementioned configurations, we have also engineered an iteration of the Low Computation Convolution (LCC) that is capable of eliminating redundant information prior to the feature extraction process in LF images. This design aims to mitigate superfluous computations, thereby enhancing computational efficiency. Experimental results show that our approach achieves suboptimal performance compared to other state-of-the-art models, while having fewer parameters, lower computational complexity, and faster inference speed. [ABSTRACT FROM AUTHOR]

With the development and popularization of unmanned aerial vehicle (UAV) equipment, UAV-based remote sensing technology has developed rapidly. With UAV aerial photography platforms, the obtained low altitude remote sensing images of surfaces have high temporal and spatial resolution and can be used for monitoring and change analyses of surface geographic information. As it is impractical to carry complex and large load equipment on a UAV, it is desirable to develop embedded systems for relevant real-time processing with UAV remote sensing technology. This study combines the advantages of UAV remote sensing image processing and embedded development technology to develop a near real-time UAV remote sensing image change detection system, which realizes the fast, accurate, and automatic detection of variations in the target area. Finally, the feasibility, correctness, and practicability of the prototype system are demonstrated with experiments. [ABSTRACT FROM AUTHOR]

The mesoscope has emerged as a powerful imaging tool in biomedical research, yet its high cost and low resolution have limited its broader application. Here, we introduce the Omni-Mesoscope, a high-spatial-temporal and multimodal mesoscopic imaging platform built from cost-efficient off-the-shelf components. This system uniquely merges the capabilities of label-free quantitative phase microscopy to capture live-cell morphodynamics across thousands of cells with highly multiplexed fluorescence imaging for comprehensive molecular characterization. This Omni-Mesoscope offers a mesoscale field of view of ~5 square millimeters with a high spatial resolution down to 700 nanometers, enabling the capture of detailed subcellular features. We demonstrate its capability in delineating molecular characteristics underlying rare morphodynamic cellular phenomena, including cancer cell responses to chemotherapy and the emergence of polyploidy in drug-resistant cells. We also integrate expansion technique to enhance three-dimensional volumetric super-resolution imaging of thicker tissues, opening the avenues for biological exploration at unprecedented scales and resolutions. [ABSTRACT FROM AUTHOR]

Universal access to childhood vaccination is important to child health and sustainable development. Here we identify, at a fine spatial scale, under-immunized children and zero-dose children. Using Chad, as an example, the most recent nationally representative household survey that included recommended vaccine antigens was assembled. Age-disaggregated population (12–23 months) and vaccination coverage were modelled at a fine spatial resolution scale (1km × 1 km) using a Bayesian geostatistical framework adjusting for a set of parsimonious covariates. There was a variation at fine spatial scale in the population 12–23 months a national mean of 18.6% (CrI 15.8%–22.6%) with the highest proportion in the South-East district of Laremanaye 20.0% (14.8–25.0). Modelled coverage at birth was 49.0% (31.2%–75.3%) for BCG, 44.8% (27.1–74.3) for DTP1, 24.7% (12.5–46.3) for DTP3 and 47.0% (30.6–71.0) for measles (MCV1). Combining coverage estimates with the modelled population at a fine spatial scale yielded 312,723 (Lower estimate 156055–409266) zero-dose children based on DTP1. Improving routine immunization will require investment in the health system as part of enhancing primary health care. The uncertainties in our estimates highlight areas that require further investigation and higher quality data to gain a better understanding of vaccination coverage. [ABSTRACT FROM AUTHOR]

The manipulation and detection of mobile domain walls in nanoscopic magnetic wires underlies the development of multibit memories. The studies of such domain walls have focused on macroscopic wires that allow for optical detection by using magneto-optic effects. In this study, we demonstrated the electrical tracking with a spatial resolution of better than 40 nm of multiple mobile domain walls in nanoscopic racetracks, using a set of anomalous Hall detectors integrated into the racetracks. Electrical time-series signals from the Hall detectors allow for the static and dynamic phase space visualization of the dynamics of a domain wall or multiple domain walls that can be described by a multicore memristor model. The domain wall dynamics and stochasticity can be controlled in racetracks even to deep submicron dimensions. [ABSTRACT FROM AUTHOR]

Mid-crustal magma domains are the source of many basaltic eruptions. Lavas from individual eruptions are often chemically homogeneous, suggesting that they derive from single, well-mixed magma reservoirs. The 2023 to 2024 eruptions at Sundhnúksgígar in the Svartsengi volcanic system in Iceland provide an opportunity to observe the behavior of a mid-crustal magma domain at high spatial and temporal resolution by detailed sampling and geochemical characterization. We observed substantial mantle-derived geochemical variability in the products erupted in the first hours of the December 2023 and January, February, and March to May 2024 eruptions, indicating that the eruptions derived from multiple magma reservoirs, which mineral-melt equilibration pressures place in the mid crust. The unusual presence of geochemical heterogeneity in the mid-crustal magma domain provides insights into how dynamic and complex mid-crustal magma domains can be. [ABSTRACT FROM AUTHOR]

In single-site validations, site-pixel, synthetic pixel and footprint-integrated methods are commonly used to validate evapotranspiration (ET) retrieval at the pixel scale. To reveal the reliability of these methods, this study analysed the performance of the three methods for ET retrieval validation based on eddy-covariance observations at the Daman site which is numerously used for validation in Heihe Watershed Allied Telemetry Experimental Research (HiWATER). The analysis at different spatial scales in different seasons showed that the validation results of the site-pixel method were more similar that of the footprint-integrated method than the synthetic pixel method. However, the validation results of the site-pixel method showed significant discrepancies from those of the footprint-integrated method, especially in summer at the 480 M scale which is near to the spatial resolution of MODIS with a large difference of more than 125.65 W M−2. This error is due to aggregation and high spatial heterogeneity. The use of synthetic pixel can avoid this error. Normally, the error probably appears when the wind direction is 270°–360°, usually in summer, autumn and winter. In addition, the different aggregation methods had a slight effect on the ET estimation results. This study is helpful in determining the reliability of different single-point validation methods and provides a reliable way to select a validation method for single-site validation of remote sensing retrieval of ET. [ABSTRACT FROM AUTHOR]

This study presents the spatial interactions downscaling (SPID) method and introduces the climate data for adaptation and vulnerability assessments (ClimAVA) dataset. SPID employs random forest models to capture the relationship between spatial patterns at global circulation model (GCM) resolution and fine-resolution pixel values. In summary, a random forest model is trained for each fine spatial resolution pixel of the reference data as the predictand, and nine pixels from the spatially resampled (coarser) version of the reference data at the GCM's resolutions as predictors. Models are then utilized to downscale the bias-corrected GCM data. The ClimAVA-SW dataset offers a high-resolution (4 km), bias-corrected, downscaled future climate projection derived from seventeen CMIP6 GCMs. It includes three variables (daily precipitation, minimum and maximum temperature) for three shared socioeconomic pathways (SSP245, SSP370, SSP585) across the U.S. Southwest region. The ClimAVA dataset sets itself apart with the SPID method's capacity to provide remarkable climate realism, high physical plausibility of change, and excellent representation of extreme events while maintaining user-friendliness and requiring relatively low computational resources. [ABSTRACT FROM AUTHOR]

Long‐term genetic studies of wild populations are very scarce, but are essential for connecting ecological and population genetics models, and for understanding the dynamics of biodiversity. We present a study of a wild wheat population sampled over a 36‐year period at high spatial resolution. We genotyped 832 individuals from regular sampling along transects during the course of the experiment. Genotypes were clustered into ecological microhabitats over scales of tens of metres, and this clustering was remarkably stable over the 36 generations of the study. Simulations show that it is difficult to determine whether this spatial and temporal stability reflects extremely limited dispersal or fine‐scale local adaptation to ecological parameters. Using a common‐garden experiment, we showed that the genotypes found in distinct microhabitats differ phenotypically. Our results provide a rare insight into the population genetics of a natural population over a long monitoring period. [ABSTRACT FROM AUTHOR]

The importance of microvascular imaging in diagnosis and therapeutic targeting of various diseases is increasingly recognized. The new approach emphasizes the need for holistic studies to understand the inter-organ vascular cross-talk. Here, we report on the development of a novel perfusion protocol which consistently delivers a micro-computed tomography contrast agent to micro-vessels of multiple organs in a single experimental animal. We describe the achieved repeatability of the perfusions, as well as the image analysis steps developed individually for each organ type. We also optimize image acquisition by investigating the compromise between shortening of the scanning time and preservation of the highest possible spatial resolution. Taking together, with the multi-organ perfusion, optimized image acquisition, and the conceived image analysis steps, we provide a comprehensive and reliable experimental protocol for studying vascular morphology and pathology in multi-organ diseases. [ABSTRACT FROM AUTHOR]

Background Purpose Methods Results Conclusion Digital tomosynthesis has shown potential for increasing specificity and sensitivity compared to radiography for low‐dose chest imaging. Prior investigation of the s‐DCT system indicated potential, but additional iteration with improved scan speed, power, and angular span was necessary for translation.The study aims to demonstrate and characterize a second‐generation stationary digital chest tomosynthesis (s‐DCT) scanner with increased x‐ray energy, tube current, and larger angular span.The second‐generation s‐DCT system employed a meter‐long linear carbon nanotube (CNT) source array integrated with a digital detector and patient imaging table. Tube output, focal spot size, modulation transfer function (MTF), artifact spread function (ASF), and imaging performance were evaluated. A lung phantom with simulated nodules was imaged for clinical task‐based demonstration.The scanner achieved a 6 s scan time, significantly improved from the prior generation's 16 s. The x‐ray tube exhibited good current stability, with 20.4 ± 0.6 mA tube current and focal spot size aligned with specifications (IEC 0.8). The MTF confirmed enhanced spatial resolution of 2.4 lp/mm, comparable to commercial chest tomosynthesis systems. The ASF indicated improved depth resolution (5.2 mm, previously 9.5 mm). Phantom imaging showcased visualization of both high and low‐attenuation lung nodules.The second‐generation s‐DCT system exhibited improved performance in terms of tube power, scan time, and image quality. Enhanced in‐plane and depth resolution, along with faster imaging, suggest potential clinical benefits for improved diagnoses. Further clinical validation is warranted to ascertain the system's clinical utility. [ABSTRACT FROM AUTHOR]

Anticipating the effects of global change on biodiversity has become a global challenge requiring new methods. Approaches like species distribution models have limitations which have fueled the development of joint species distribution models (JSDMs). However, JSDMs rely on systematic surveys community data, and no assessment has been made of their suitability with unstructured opportunistic databases data. We used hierarchical modeling of species communities (HMSC) to test JSDMs performance when using opportunistic databases. Using artificial data that mimic the limitations of such databases by subsampling complete co‐occurrence matrices (i.e. original data), we analysed how the completeness of opportunistic databases affects JSDMs regarding 1) the role of independent variables on species occurrence, 2) residual species co‐occurrence (as a proxy of biotic interactions) and 3) species distributions. Moreover, we illustrate how to evaluate completeness at the pixel level of real data with a study case of forest tree species in Europe, and evaluate the role of data completeness in model estimation. Our results with artificial data demonstrate that decreasing the completion percentage (the rate of original data presences represented in the subsampled matrices) increases false negatives and negative co‐occurrence probabilities, resulting in a loss of ecological information. However, HMSC tolerates different levels of degradation depending on the model aspect being considered. Models with 50% of missing data are valid for estimating species niches and distribution, but interaction matrices require databases with at least 75% of completion data. Furthermore, HMSC's predictions often resemble the original community data (without false negatives) even more than the subsampled data (with false negatives) in the training dataset. These findings were confirmed with the real study case. We conclude that opportunistic databases are a valuable resource for JSDMs, but require an analysis of data completeness for the target taxa in the study area at the spatial resolution of interest. [ABSTRACT FROM AUTHOR]

Generative models, such as diffusion models, have made significant advancements in recent years, enabling the synthesis of high‐quality realistic data across various domains. Here, the adaptation and training of a diffusion model on super‐resolution microscopy images are explored. It is shown that the generated images resemble experimental images, and that the generation process does not exhibit a large degree of memorization from existing images in the training set. To demonstrate the usefulness of the generative model for data augmentation, the performance of a deep learning‐based single‐image super‐resolution (SISR) method trained using generated high‐resolution data is compared against training using experimental images alone, or images generated by mathematical modeling. Using a few experimental images, the reconstruction quality and the spatial resolution of the reconstructed images are improved, showcasing the potential of diffusion model image generation for overcoming the limitations accompanying the collection and annotation of microscopy images. Finally, the pipeline is made publicly available, runnable online, and user‐friendly to enable researchers to generate their own synthetic microscopy data. This work demonstrates the potential contribution of generative diffusion models for microscopy tasks and paves the way for their future application in this field. [ABSTRACT FROM AUTHOR]

Monocular depth estimation is an important but challenging task. Although the performance has been improved by adopting various encoder-decoder architectures, the estimated depth maps lack structure details and clear edges due to simple repeated upsampling. To solve this problem, this paper presents the novel LapUNet (Laplacian U-shape networks), in which the encoder adopts ResNeXt101, and the decoder is constructed with the novel DLRU (dynamic Laplacian residual U-shape) module. The DLRU module based on the U-shape structure can supplement high-frequency features by fusing dynamic Laplacian residual into the process of upsampling, and the residual is dynamically learnable due to the addition of convolutional operation. Also, the ASPP (atrous spatial pyramid pooling) module is introduced to capture image context at multiple scales though multiple parallel atrous convolutional layers, and the depth map fusion module is used for combining high and low frequency features from depth maps with different spatial resolution. Experiments demonstrate that the proposed model with moderate model size is superior to other previous competitors on the KITTI and NYU Depth V2 datasets. Furthermore, 3D reconstruction and target ranging by utilizing the estimated depth maps prove the effectiveness of our proposed method. [ABSTRACT FROM AUTHOR]

In Brillouin optical correlation-domain reflectometry (BOCDR), sinusoidal modulation is applied to the output frequency of a light source, with spatial resolution inversely related to the modulation amplitude. We have developed an effective method to estimate the modulation amplitude using the width of the noise spectrum caused by Rayleigh scattering, eliminating the need for an optical spectrum analyzer or modifications to existing equipment. However, the Rayleigh noise spectrum often displays a three-layered structure, complicating the identification of the appropriate spectral components for estimating the modulation amplitude. In this work, we investigate the origins of this three-layered Rayleigh noise spectrum and identify the directivity of an optical circulator as the source of the third noise component. As replacing the circulator with alternative optical components is not easy, it remains an essential part of the system. Our analysis shows that the third noise component exhibits significantly small variation in spectral width with changes in modulation frequency compared to the first and second components. This characteristic allows for the effective separation and identification of the third noise component, thereby enhancing the accuracy and convenience of modulation amplitude estimation in BOCDR. [ABSTRACT FROM AUTHOR]

Manipulating ferromagnetic particles using an alternating current (AC) magnetic field is a versatile method for quick, local, and on‐demand heat generation. These particles can be incorporated into various matrices as heating elements. Their heat release can be controlled by adjusting process or material parameters. Herein, a proof‐of‐concept for a flexible polymer composite with customizable magnetically triggered heat release due to prior object identification via fluorescence readout is presented. The maximum temperature resulting from this process can be determined through a second fluorescence readout ex post. This novel combination of functionalities results from the synergistic interaction of inductively heatable magnetic supraparticles (SPs) and luminescent communicating SPs in one polydimethylsiloxane composite. The surface of the composite can be heated to the maximum temperatures of choice in a range between 125 and 200 °C within 2 s. Heat release and temperature verification provide spatial resolution of millimeters. The identification signature and the working range of the temperature indication functionality of the composite are customizable by exploiting its modular material design. The temperature indication functionality of the composite offers spatial resolution and ex‐post readout at any point of interest, making it a versatile alternative to established optical thermometry methods. [ABSTRACT FROM AUTHOR]

Improving the sustainability of the European livestock sector requires recent data at high spatial resolutions. Only then can we analyse potential negative impacts of livestock related to ecosystem degradation, and positive ones such as preserving cultural landscapes through grazing. Data on livestock numbers in Europe are provided by the European statistical office but at a coarse spatial resolution aggregated to statistical regions like NUTS2 or even coarser. While data on a more detailed level, such as local administrative areas, are available from individual national statistical offices, a collection of harmonized data has not been available until now, limiting the use of livestock data in environmental and agricultural studies. We collected data from all European Union Member States and neighbouring countries, resulting in the most up to date and spatially explicit dataset on livestock numbers publicly available to all researchers. We provide data on livestock numbers for more than 70,000 administrative units in 43 countries and territories. In addition, we provide data on the share of cattle that are grazing. [ABSTRACT FROM AUTHOR]

A high-accuracy, continuous air temperature (Ta) dataset with high spatiotemporal resolution is essential for human health, disease prediction, and energy management. Existing datasets consider factors such as elevation, latitude, and surface temperature but insufficiently address meteorological and spatiotemporal factors, affecting accuracy. Additionally, no high-resolution dataset currently includes daily maximum (Tmax), minimum (Tmin), and mean (Tmean) temperatures generated using a unified methodology. Here, we introduce the four-dimensional spatiotemporal deep forest (4D-STDF) model, integrating 12 multisource factors, encompassing static and dynamic parameters, and six refined spatiotemporal factors to produce Ta datasets. This approach generates three high-accuracy Ta datasets at 1 km spatial resolution covering mainland China from 2003 to 2022. These datasets, in GeoTIFF format with WGS84 projection, comprise daily Tmax, Tmin, and Tmean. The overall RMSE are 1.49 °C, 1.53 °C, and 1.18 °C for the estimates. The 4D-STDF model can also be applied to other regions with sparse meteorological stations. [ABSTRACT FROM AUTHOR]

The spatial distribution and data quality of curve number (CN) values determine the performance of hydrological estimations. However, existing CN datasets are constrained by universal-applicability hypothesis, medium resolution, and imbalance between specificity CN tables to generalized land use/land cover (LULC) maps, which hinder their applicability and predictive accuracy. A new annual CN dataset named CUSCN30, featuring an enhanced resolution of 30 meters and accounting for temporal variations in climate and LULC in the continental United States (CONUS) between 2008 and 2021, was developed in this study. CUSCN30 demonstrated good performance in surface runoff estimation using CN method when compared to observed surface runoff for the selected watersheds. Compared with existing CN datasets, CUSCN30 exhibits the highest accuracy in runoff estimation for both normal and extreme rainfall events. In addition, CUSCN30, with its high spatial resolution, better captures the spatial heterogeneity of watersheds. This developed CN dataset can be used as input for hydrological models or machine learning algorithms to simulate rainfall-runoff across multiple spatiotemporal scales. [ABSTRACT FROM AUTHOR]

Satellite altimetry is the main tool for constructing global or regional marine gravity fields. To improve the accuracy and spatial resolution, it is necessary to fuse multi-mission altimeters. How to determine the weights of multi-mission altimeters is a crucial issue, making the conventional calculation process very complex. In addition, traditional satellite inversion methods are often independent of shipborne gravity, which is used only as validation data, thus not take full advantages of high accuracy and resolution of shipborne gravity. In this study, we introduce a convolutional neural network (CNN) to merge the vertical deflections (DOVs) obtained from multi-altimeter missions to construct a marine gravity model in the South China Sea. High-accuracy shipborne gravity and a dataset comprising DOVs and geo-locations are employed as input data for neural network training. For the validation of CNN method, the gravity model is also computed by conventional Inverse Vening Meinesz (IVM) method. Independent shipborne gravity measurements and SIO V32.1, DTU17 models are used as validation data. The evaluation results show that the CNN-derived model achieves a higher level of accuracy, yielding a standard deviation (STD) of 3.21 mGal, with an improvement of 36.56% compared to IVM-derived model. More than 92% of the differences between the CNN-derived model and shipborne gravity are less than 5 mGal. In addition, spectral analysis results further show that the CNN-derived model has stronger energy at short wavelengths (less than 25 km) compared to other models. These findings reveal that CNN method is feasible for marine gravity recovery and the CNN-derived model can achieve higher accuracy. The CNN method can improve the accuracy and spectral characteristics of the constructed gravity model by taking advantage of the high accuracy and high resolution of shipborne gravity. [ABSTRACT FROM AUTHOR]

In this work, we propose a structured-illumination lensless digital holographic microscopy (SI-LDHM). SI-LDHM illuminates a sample with 24 structured illuminations (8 orientations χ 3 phase shifts) and records the defocused interferogram formed by two copies of object waves along the ±1st diffraction orders of each SI. The reconstructed object waves under different illumination orientations are respectively propagated to the sample plane along the +1st diffraction order and then averaged, thus yielding a clean image without the artifact of twin images. Experimental results demonstrated that thanks to the multi-oriented SI strategy, the twin image in SI-LDHM is sevenfold reduced compared to conventional DHM, while the spatial resolution is 1.15 times higher. [ABSTRACT FROM AUTHOR]

Highly sensitive airborne virus monitoring is critical for preventing and containing epidemics. However, the detection of airborne viruses at ultra-low concentrations remains challenging due to the lack of ultra-sensitive methods and easy-to-deployment equipment. Here, we present an integrated microfluidic cartridge that can accurately detect SARS-COV-2, Influenza A, B, and respiratory syncytial virus with a sensitivity of 10 copies/mL. When integrated with a high-flow aerosol sampler, our microdevice can achieve a sub-single-copy spatial resolution of 0.83 copies/m3 for airborne virus surveillance with an air flow rate of 400 L/min and a sampling time of 30 minutes. We then designed a series of virus-in-aerosols monitoring systems (RIAMs), including versions of a multi-site sampling RIAMs (M-RIAMs), a stationary real-time RIAMs (S-RIAMs), and a roaming real-time RIAMs (R-RIAMs) for different application scenarios. Using M-RIAMs, we performed a comprehensive evaluation of 210 environmental samples from COVID-19 patient wards, including 30 aerosol samples. The highest positive detection rate of aerosol samples (60%) proved the aerosol-based SARS-CoV-2 monitoring represents an effective method for spatial risk assessment. The detection of 78 aerosol samples in real-world settings via S-RIAMs confirmed its reliability for ultra-sensitive and continuous airborne virus monitoring. Therefore, RIAMs shows the potential as an effective solution for mitigating the risk of airborne virus transmission. Effective surveillance of respiratory virus particles in air requires highly sensitive tools that can produce timely and accurate results. Here, the authors develop a device for detection of four respiratory viruses in air with high spatial viral resolution and test it in different settings. [ABSTRACT FROM AUTHOR]

The human thermal stress indices and datasets are vital for promoting public health and reducing negative environmental impacts as global climate change and extreme meteorological events increase. The current thermal indices generally use an instantaneous or average value to describe thermal stress which cannot reflect the distribution of thermal comfort conditions over time, and there are no global-scale thermal stress datasets with both 0.1° or higher spatial resolution and hourly temporal resolution available yet. A novel human thermal metric, Thermal Stress Duration (TSD), is proposed to represent the accumulative time of different thermal stress levels within a certain period. A high temporal resolution global gridded dataset of human thermal stress metrics (HiGTS) is presented, which consists of hourly gridded maps of Universal Thermal Climate Index (UTCI), Universal Thermal Stress (UTS), and daily TSD at 0.1° × 0.1° spatial resolution over the global land surface, spanning from January 1, 2000, to December 31, 2023. [ABSTRACT FROM AUTHOR]