Spatial Variation In Density Research Articles

Deep learning framework for automated goblet cell density analysis in in-vivo rabbit conjunctiva

Goblet cells (GCs) in the conjunctiva are specialized epithelial cells secreting mucins for the mucus layer of protective tear film and playing immune tolerance functions for ocular surface health. Because GC loss is observed in various ocular surface diseases, GC examination is important for precision diagnosis. Moxifloxacin-based fluorescence microscopy (MBFM) was recently developed for non-invasive high-contrast GC visualization. MBFM showed promise for GC examination by high-speed large-area imaging and a robust analysis method is needed to provide GC information. In this study, we developed a deep learning framework for GC image analysis, named dual-channel attention U-Net (DCAU-Net). Dual-channel convolution was used both to extract the overall image texture and to acquire the GC morphological characteristics. A global channel attention module was adopted by combining attention algorithms and channel-wise pooling. DCAU-Net showed 93.1% GC segmentation accuracy and 94.3% GC density estimation accuracy. Further application to both normal and ocular surface damage rabbit models revealed the spatial variations of both GC density and size in normal rabbits and the decreases of both GC density and size in damage rabbit models during recovery after acute damage. The GC analysis results were consistent with histology. Together with the non-invasive high-contrast imaging method, DCAU-Net would provide GC information for the diagnosis of ocular surface diseases.

Coalescence-Induced Droplet Jumping on Superhydrophobic Surfaces with Annular Wedge-Shaped Micropillar Arrays.

The coalescence-induced droplet jumping on superhydrophobic surfaces has extensive application potential in water harvesting, thermal management of electronic devices, and microfluidics. The rational design of the surface structure can influence the interaction between the droplet and the surface, thereby controlling the velocity and direction of the droplet's jumping. In this study, we fabricate the superhydrophobic surface with annular wedge-shaped micropillar arrays, examine the dynamic behavior of condensate droplets on the surface, and measure the temporal and spatial variations of droplet density, average radius, and surface coverage with wedge-shaped micropillars of varying sizes. In addition, the energy analysis of the coalescence-induced droplet jumping reveals that the two primary factors influencing the jumping are the relative size and position of the droplets and micropillars. Further numerical simulations find that the wedge-shaped micropillars cause an asymmetric distribution of pressure within the droplet and at the solid-liquid contact surface, which generates an unbalanced force driving the droplet in the gradient direction of the wedge-shaped micropillar, causing the droplet to jump off the surface with both vertical and gradient-direction velocities. The capacity of the wedge-shaped micropillar surface to transport droplets in the gradient direction increases and then decreases as the relative size of the droplets and micropillars increases. The relative position of the droplet center-of-mass line perpendicular to the bottom edge of the wedge micropillars' trapezoidal shape is more favorable for droplet transport. This work reveals the influence mechanism of surface structure on the velocity and direction of droplet jumping, and the results can guide the microstructure design of superhydrophobic surfaces, which has significant implications for the application of droplet jumping.

Variations in thermospheric density during two consecutive geomagnetic storms of different solar wind conditions in November 2022

Geomagnetic storms can cause severe space weather impacts on space technology, such as anomaly and loss of satellites and spacecraft. We investigate solar wind conditions in responsible for two consecutive geomagnetic storms driven by different sources: a high-speed solar wind stream (HSS) on November 3-4, 2022, and a coronal mass ejection (CME) associated with an M5.2 solar flare on November 7, 2022. Spatial and temporal variations in thermospheric density and auroral activity are studied for the two geomagnetic storms. Measurements from the Swarm satellite show that the HSS-driven geomagnetic storm enhanced the thermospheric density by ~69.4% at 462 km and by ~92.8% at 511 km, and the CME-driven geomagnetic storm enhanced it by ~99.4% at 462 km and by ~145% at 511 km. Images taken by the F17 DMSP/SSUSI indicate the auroral emission produced by CME-driven geomagnetic storm is significantly stronger than that produced by HSS-driven storm, while the HSS-driven auroras last longer than the CME-driven ones. The correlation between the hourly moving averaged SymH data and the thermospheric density is stronger for Swarm-A than for Swarm-B. The response times of the thermospheric density for the HSS-driven geomagnetic storm are zero at 462 km and ~47 minutes at 511 km, while for the CME-driven geomagnetic storm are ~28 minutes and ~35 minutes, respectively. This study sheds light on the mechanisms underlying the change in the thermospheric density in relation to different geomagnetic activities.

The influence of environmental parameters on spatial variation in zoobenthic density and stable isotopes (δ13C, δ15N, and δ34S) within a large lake

AbstractThe use of baselines in stable isotope studies to interpret food web structure is essential, but baseline isotope values are often assumed to be spatially homogeneous, even in large aquatic ecosystems. To test this assumption in large lakes, we quantified spatial variation in δ13C, δ15N (deposit‐feeding Oligochaeta and filter‐feeding Dreissena spp.), and δ34S (Dreissena spp. only) and density in Lake Erie between 2014 and 2016. Lake Erie's three distinct basins differ in size, bathymetry, and nutrient loading, making it an excellent system for exploring spatial variation in stable isotopes of baseline organisms. Dreissena spp. densities were highest in the western and lowest in the seasonally hypoxic central basin, while Oligochaeta densities were relatively consistent throughout Lake Erie. Values of δ13C, δ15N, and δ34S exhibited distinct spatial trends that were not related to population densities but followed the west to east direction of water flow within the lake. For both taxa, δ13C was lower in the deeper, oligotrophic east basin than the shallow, mesotrophic west basin, and δ15N and δ34S increased from west to east. Spatial patterns of low δ34S in Dreissena spp. in the western and central basins were likely related to hypoxia, whereas patterns of δ15N in both taxa were probably related to the greater influence of agricultural land uses in the western basin. Spatial trends of stable isotopes in large lake zoobenthos are driven by complex interactions of environmental gradients, which could introduce bias in evaluations of trophic structures within aquatic ecosystems that use stable isotopes.

Compaction-induced variability in the 80/20 sand-bentonite mixture: Spatial variation in dry density at different scales in the laboratory and large-scale gas seal test

Sand-bentonite (SB) mixtures are considered as backfill materials for sealing designated sections of nuclear waste repositories. The dry density of the SB mixture is the crucial parameter for the quality control during emplacement because it strongly controls the hydraulic and mechanical properties. Backfilling of an SB mixture is often performed layer by layer by keeping track of the average dry density of each layer. The compaction is typically done in a dynamic manner leading to more compaction near the compaction surface. In this study, an SB mixture with 80% sand and 20% bentonite was compacted in the laboratory by static and dynamic procedures to a height of 10 cm and the dry density profile was characterized by destructive slicing and microfocus X-ray CT imaging. When dynamically compacted, a distinct dry density gradient was identified. The variation in the dry density identified by the slicing was as much as 0.4 g/cm3 which leads to hydraulic conductivity variation by a factor of 4.8. The SB seal emplaced in the large-scale gas seal test (GAST) for demonstrating the effective functioning of the gas permeable seals was also analyzed to identify if any variability was present at the field scale. The samples collected from the top 2 cm of each 10 cm-thick horizontal layers yielded a higher overall average by 0.06 g/cm3 than the average of the mass balance method. In conjunction with the laboratory studies, it was implied that sampling results, if only collected from the very top few centimeters of the layers, could lead to an overestimation in the global dry density. Overall, the results with different methods at different scales indicated that the dynamic compaction-induced variability within a single layer was more pronounced than the variability in the larger scales detected in the mass balance and sampling methods.

Mapping urban living standards and economic activity in developing countries with energy data.

Urban data deficits in developing countries impede evidence-based planning and policy. Could energy data be used to overcome this challenge by serving as a local proxy for living standards or economic activity in large urban areas? To answer this question, we examine the potential of georeferenced residential electricity meter data and night-time lights (NTL) data in the megacity of Karachi, Pakistan. First, we use nationally representative survey data to establish a strong association between electricity consumption and household living standards. Second, we compare gridded radiance values from NTL data with a unique dataset containing georeferenced median monthly electricity consumption values for over 2 million individual households in the city. Finally, we develop a model to explain intra-urban variation in radiance values using proxy measures of economic activity from Open Street Map. Overall, we find that NTL data are a poor proxy for living standards but do capture spatial variation in population density and economic activity. By contrast, electricity data are an excellent proxy for living standards and could be used more widely to inform policy and support poverty research in cities in low- and middle-income countries.

Spatial variation in density of American black bears in northern Yellowstone National Park

AbstractThe quality and availability of resources are known to influence spatial patterns of animal density. In Yellowstone National Park, relationships between the availability of resources and the distribution of grizzly bears (Ursus arctos) have been explored but have yet to be examined in American black bears (Ursus americanus). We conducted non‐invasive genetic sampling during 2017–2018 (mid‐May to mid‐July) and applied spatially explicit capture‐recapture models to estimate density of black bears and examine associations with landscape features. In both years, density estimates were higher in forested vegetation communities, which provide food resources and thermal and security cover preferred by black bears, compared with non‐forested areas. In 2017, density also varied by sex, with female densities being higher than males. Based on our estimates, the northern range of Yellowstone National Park supports one of the highest densities of black bears (20 black bears/100 km2) in the northern Rocky Mountains (6–12 black bears/100 km2 in other regions). Given these high densities, black bears could influence other wildlife populations more than previously thought, such as through displacement of sympatric predators from kills. Our study provides the first spatially explicit estimates of density for black bears within an ecosystem that contains the majority of North America's large mammal species. Our density estimates provide a baseline that can be used for future research and management decisions of black bears, including efforts to reduce human–bear conflicts.

Inferring bovine tuberculosis transmission between cattle and badgers via the environment and risk mapping.

Bovine tuberculosis (bTB), caused by Mycobacterium bovis, is one of the most challenging and persistent health issues in many countries worldwide. In several countries, bTB control is complicated due to the presence of wildlife reservoirs of infection, i.e. European badger (Meles meles) in Ireland and the UK, which can transmit infection to cattle. However, a quantitative understanding of the role of cattle and badgers in bTB transmission is elusive, especially where there is spatial variation in relative density between badgers and cattle. Moreover, as these two species have infrequent direct contact, environmental transmission is likely to play a role, but the quantitative importance of the environment has not been assessed. Therefore, the objective of this study is to better understand bTB transmission between cattle and badgers via the environment in a spatially explicit context and to identify high-risk areas. We developed an environmental transmission model that incorporates both within-herd/territory transmission and between-species transmission, with the latter facilitated by badger territories overlapping with herd areas. Model parameters such as transmission rate parameters and the decay rate parameter of M. bovis were estimated by maximum likelihood estimation using infection data from badgers and cattle collected during a 4-year badger vaccination trial. Our estimation showed that the environment can play an important role in the transmission of bTB, with a half-life of M. bovis in the environment of around 177 days. Based on the estimated transmission rate parameters, we calculate the basic reproduction ratio (R) within a herd, which reveals how relative badger density dictates transmission. In addition, we simulated transmission in each small local area to generate a first between-herd R map that identifies high-risk areas.

Spawning aggregations of checkered snapper (Lutjanus decussatus) and blackspot snapper (L. fulviflamma): seasonality, lunar-phase periodicity and spatial distribution within spawning ground.

Snappers (family Lutjanidae) are important fisheries target species and some species are known to form spawning aggregations at particular spawning grounds. The present study investigated the ecological characteristics of fish aggregations of two snapper species (checkered snapper Lutjanus decussatus and blackspot snapper L. fulviflamma) that form at a particular site. Specifically, the aims were to clarify (1) seasonality and lunar-phase periodicity of fish aggregation formation, (2) fine-scale spatial distribution of fish density (spatial variations of fish density at intervals of several-tens meters) within the aggregation site, (3) size and age frequency distributions of fishes in the aggregation site, (4) gonad development, (5) to compare fish abundance between inside and outside the aggregation site, and (6) to verify that fish aggregations of the two snapper species were spawning aggregation. Underwater observations using a 600m×5m transect revealed that greater fish abundance of Lutjanus decussatus was found monthly between May and October, and clear positive peaks in the fish abundance were found only around the last-quarter moon. This lunar-related periodicity in the increase of fish abundance was confirmed by a time-series analysis (correlogram). Within the aggregation site, L. decussatus showed a relatively uniform distribution. In contrast, greater fish abundance of L. fulviflamma was found monthly between April and October, and clear positive peaks in the fish abundance were found around the last-quarter moon (April, May, June and October) or new moon (July, August and September). This lunar-related periodicity was also confirmed by correlogram. Lutjanus fulviflamma showed a relatively clumped distribution within the aggregation site. Most females of the two species in the aggregation site had hydrated eggs, indicating that the two species form aggregations for reproduction. The two species, although occurring simultaneously, are considered to form aggregations of conspecifics only. For L. decussatus, average fork length and age of males and females were 229.2 mm and 243.9 mm and 9.4 years and 8.1 years, respectively. For L. fulviflamma, average fork length and age of males and females were 233.9 mm and 246.9 mm and 6.8 years and 8.1 years, respectively. Fish abundance inside the aggregation site was 266.8-fold and 141557.1-fold greater than those outside the aggregation site for L. decussatus and L. fulviflamma, respectively. These results showed that (1) fish aggregation formation of the two snapper species was predictably repeated in particular months and lunar-phase, (2) it was predictably found at the particular site, (3) the fish abundance in the aggregation site markedly exceeded the fish abundance outside the aggregation site, and (4) the two species form aggregations for reproduction. Therefore, it is suggested that the fish aggregations for the two species can be regarded as spawning aggregations.

High densities, rapid infestation and high feeding rates of corallivore gastropods on corals in Bora-Bora Island, French Polynesia

The global decline of coral reefs has prompted research into understanding the impacts of anthropogenic stressors, as well as the interactions between corals and their natural predators, especially those that proliferate into outbreaks. However, studies on gastropod corallivores are lagging behind. The present study, conducted on Bora-Bora (French Polynesia), focused on two genera of corallivore muricid gastropods: Drupella spp. living on Acropora colonies and Coralliophila violacea on Porites rus colonies. An observational experiment of Drupella spp. and C. violacea showed strong spatial variation in densities across different habitats (fringing reef, channel, barrier reef) in Bora-Bora lagoon. The highest densities found were 21 ± 6 ind.m−3 of coral for Drupella spp. on the fringing reef, and 342 ± 51 ind.m−3 for C. violacea on the barrier reef. A manipulation experiment monitored the infestation dynamics of these gastropods. For both genera, colonization of vacant coral colonies was rapid during the first 14 days and then stabilized over the next 42 days. The manipulation experiment showed that the feeding rate on live and healthy coral tissue did not change significantly with Drupella spp. density (0.6 ± 0.2 cm 2/day/ind for 1 Drupella spp., and 0.5 ± 0.1 cm 2/day/ind for 5 Drupella spp.). Overall, our study highlights the high densities of two gastropod species, their rapid movement and infestation of vacant colonies and their role in the necrosis of corals during feeding. In view of the possible outbreaks involving high densities of such predatory gastropods in a major tourist destination in the Pacific Ocean, human resources could be put in place to manually remove these gastropods in a sustainable manner, but this would require a lot of effort in terms of manpower and time. Nature-based solutions such as the conservation of natural predators should be considered to prevent large-scale destructions by these gastropod aggregations.

Patternshop: Editing Point Patterns by Image Manipulation

Point patterns are characterized by their density and correlation. While spatial variation of density is well-understood, analysis and synthesis of spatially-varying correlation is an open challenge. No tools are available to intuitively edit such point patterns, primarily due to the lack of a compact representation for spatially varying correlation. We propose a low-dimensional perceptual embedding for point correlations. This embedding can map point patterns to common three-channel raster images, enabling manipulation with off-the-shelf image editing software. To synthesize back point patterns, we propose a novel edge-aware objective that carefully handles sharp variations in density and correlation. The resulting framework allows intuitive and backward-compatible manipulation of point patterns, such as recoloring, relighting to even texture synthesis that have not been available to 2D point pattern design before. Effectiveness of our approach is tested in several user experiments. Code is available at https://github.com/xchhuang/patternshop.

Cosmic-ray-driven enhancement of the C0/CO abundance ratio in W 51 C

Abstract We examine spatial variations of the C0$/$CO abundance ratio (XC/CO) in the vicinity of the γ-ray supernova remnant W 51 C, based on [C i] (3P1–3P0), 12CO(1–0), and 13CO(1–0) observations with the ASTE and Nobeyama 45 m telescopes. We find that XC/CO varies in a range of 0.02–0.16 (0.05 in median) inside the molecular clouds of AV > 100 mag, where photodissociation of CO by the interstellar UV is negligible. Furthermore, XC/CO is locally enhanced by a factor of up to four near the W 51 C center, depending on the projected distance from the W 51 C center. In high-AV molecular clouds, XC/CO is determined by the ratio of the cosmic-ray (CR) ionization rate to the H2 density, and we find no clear spatial variation of the H2 density against the projected distance. Hence, the high CR ionization rate may locally enhance XC/CO near the W 51 C center. We also find that the observed spatial extent of the enhanced XC/CO (∼17 pc) is consistent with the diffusion distance of CRs with an energy of 100 MeV. This fact suggests that the low-energy CRs accelerated in W 51 C enhance XC/CO. The CR ionization rate in the XC/CO-enhanced cloud is estimated to be 3 × 10−16 s−1 on the basis of time-dependent photodissociation region simulations of XC/CO, the value of which is 30 times higher than that in the standard Galactic environment. These results demonstrate that [C i] is a powerful probe to investigate the interaction between CRs and the interstellar medium for a wide area in the vicinity of supernova remnants.

Plating and Stripping of Lithium Metal Stabilized by a Block Copolymer Electrolyte: Local Current Density Measurement and Modeling

Plating and stripping of lithium protrusions in lithium metal symmetric cells containing a solid block copolymer electrolyte was studied as a function of time in 3D using time-resolved X-ray tomography. These measurements enabled determination of the spatial variation in current densities at the plating and stripping electrodes. The initial interelectrode distance was 27 μm. Correlation functions were calculated to reveal the relationships between current densities at the two electrodes and local electrolyte thickness. Current densities at opposing electrode locations during protrusion growth is uncorrelated until the local interelectrode distance decreases to less than 6 μm, just before the cell shorts. Mass balance was used to determine the area from which lithium ions that form a protrusion were stripped. Computational modeling of the plating and stripping process reveals the interplay between electrochemical and mechanical driving forces and their effect on nonuniform current distribution. Model predictions were compared with experiments without resorting to any adjustable parameters. The computed correlation functions were in qualitative agreement with experiments. Finally, the model was used to calculate contour plots of electrochemical potential within the electrolyte, shedding light on how geometry, salt concentration, interelectrode distance, and mechanical stress influence local rates of electrochemical reaction.

Turkey Vulture survival is reduced in areas of greater road density

Abstract The demography of, and factors that influence these metrics, are largely unknown for most vultures in the Americas. Survivorship of Turkey Vultures (Cathartes aura) may be influenced by landscape heterogeneity and human disturbance. We quantified the effects of landscape composition (Shannon’s diversity index) and configuration (contagion, edge density, and largest patch index), and human disturbance (road density) on the annual and seasonal survival probabilities of the three North American breeding populations (western, central, and eastern) of Turkey Vultures that spend the nonbreeding season in the southeastern portion of the Nearctic and the northern Neotropics during a 17-year period. We used Cox’s proportional hazards models with time-varying covariates to estimate spatial and temporal changes in survival rates of adult Turkey Vultures. Road density, but not landscape composition or configuration, influenced survival rates in space and time. Overall annual survival averaged 0.87 (95% confidence interval [CI]: 0.74–0.98). Mortality risk was low in western and central populations (hazard ratio < 1) but was 3.7 times greater for vultures in the eastern population. Survival during the breeding (0.97, 95% CI: 0.96–0.98) and outbound migration (1.0, 95% CI: 1–1) seasons was significantly higher than the other seasons. Average survival tended to be higher for nonbreeding (0.81, 95% CI: 0.71–0.88) compared to return migration (0.69, 95% CI: 0.56–0.81) seasons. The risk of mortality for all vulture populations increased with road density, and this was greater during the nonbreeding and return migration seasons. The spatial variation in road density across the Americas may generate a network of ecological traps for Turkey Vultures induced to stop in areas of greater road-kill abundance. Road-killed animals acting as an attractant for vultures can increase the occurrence of vulture–vehicle collisions and potentially aggravate human–wildlife conflicts. Further analyses are needed to address survivorship and mortality factors for young birds. Our results may help the implementation of specific mitigation efforts to reduce human–vulture conflicts and vulture mortality. For instance, concentrating efforts to remove road-killed animals in areas where road density is highest can likely reduce vulture–vehicle collisions and associated mortalities of these birds.

Global‐Krigger: A Global Kriging Interpolation Toolbox With Paleoclimatology Examples

AbstractMany applications in Earth sciences require spatial prediction, that is, obtaining a continuous scalar field from a set of discrete scalar data points on the Earth's surface. Such applications include model‐data comparisons and derivation of continuous scalar fields as input for Earth system models. The advantage of kriging as an interpolation method is that it provides predictions with confidence intervals for data sets of irregularly distributed points in space. However, the theory of kriging for non‐Euclidean domains such as oblate spheroids (e.g., the Earth's surface) is poorly developed, and existing kriging algorithms for global interpolation oftentimes cannot guarantee the validity of their predictions. Here, we present Global‐Krigger, a new kriging interpolation algorithm adapted for local to global applications that (a) incorporates a numerical check to guarantee that the necessary conditions for the kriging system of linear equations are met, and (b) derives a combined uncertainty field due both to spatial variations in data density and measurement error. The robustness of the method is demonstrated by cross‐validating predictions against reanalysis fields of traditional climatological scalar variables. We also show an example application in paleoclimatology for Holocene mineral dust deposition fluxes. The toolbox includes a user‐friendly graphical user interface that guides users through a range of choices during data pre‐interpolation analysis, kriging, and post‐processing.

Assessing the carbon sequestration potential and identifying influential factors of cultivated soils in Northeast China

Cultivated lands play a crucial role in terrestrial carbon cycle, and enhancing soil organic carbon (SOC) sequestration in these areas can help effectively mitigate the rise of atmospheric CO2 concentration. In this study, topsoil (0–20 cm) saturated SOC and its density of cultivated soil in Northeast China were mapped using a boosted regression trees (BRT) model. The distribution of the SOC sequestration potential was also calculated based on the difference between saturated SOC and SOC density in ArcGIS. Nine environmental factors including climate, topography and lengths of cultivation data (LCD) and 197 soil samples are used. A 10-fold cross-validation technique is applied to derive four statistical indices - mean absolute prediction error (MAE), root mean square error (RMSE), coefficient of determination (R2) and Lin's consistent correlation coefficient (LCCC) to verify the model performance. The model explains 81% and 85% of the spatial variation of saturated SOC and SOC density, respectively. Mean annual temperature and mean annual precipitation are key factors controlling SOC density and saturated SOC distribution. In addition, LCD showed a similar spatial pattern to SOC sequestration potential, influencing the distribution of SOC density and saturated SOC in the study area. We recommend LCD as an important factor to consider in saturated SOC and SOC density predictions, especially in the farmland ecosystem with a long reclamation history. Accurate mapping SOC sequestration potential and identifying environmental factors will help manage land use and promote soil quality evaluation and improve soil carbon sequestration in this region.

Spatiotemporal dynamics of functional connectivity and association with molecular architecture in schizophrenia.

Schizophrenia is a self-disorder characterized by disrupted brain dynamics and architectures of multiple molecules. This study aims to explore spatiotemporal dynamics and its association with psychiatric symptoms. Resting-state functional magnetic resonance imaging data were collected from 98 patients with schizophrenia. Brain dynamics included the temporal and spatial variations in functional connectivity density and association with symptom scores were evaluated. Moreover, the spatial association between dynamics and receptors/transporters according to prior molecular imaging in healthy subjects was examined. Patients demonstrated decreased temporal variation and increased spatial variation in perceptual and attentional systems. However, increased temporal variation and decreased spatial variation were revealed in higher order networks and subcortical networks in patients. Specifically, spatial variation in perceptual and attentional systems was associated with symptom severity. Moreover, case-control differences were associated with dopamine, serotonin and mu-opioid receptor densities, serotonin reuptake transporter density, dopamine transporter density, and dopamine synthesis capacity. Therefore, this study implicates the abnormal dynamic interactions between the perceptual system and cortical core networks; in addition, the subcortical regions play a role in the dynamic interaction among the cortical regions in schizophrenia. These convergent findings support the importance of brain dynamics and emphasize the contribution of primary information processing to the pathological mechanism underlying schizophrenia.

Investigating the linkage between mesopic spatial summation and variations in retinal ganglion cell density across the central visual field.

The relationship between perimetric stimulus area and Ricco's area (RA) determines measured thresholds and the sensitivity of perimetry to retinal disease. The nature of this relationship, in addition to effect of retinal ganglion cell (RGC) number on this, is currently unknown for the adaptation conditions of mesopic microperimetry. In this study, achromatic mesopic spatial summation was measured across the central visual field to estimate RA with the number of RGCs underlying RA also being established. Achromatic luminance thresholds were measured for six incremental spot stimuli (0.009-2.07 deg2 ) and 190.4 ms duration, at four locations, each at 2.5°, 5° and 10° eccentricity in five healthy observers (mean age 61.4 years) under mesopic conditions (background 1.58 cd/m2 ). RA was estimated using two-phase regression analysis with the number of RGCs underlying RA being calculated using normative histological RGC counts. Ricco's area exhibited a small but statistically insignificant increase between 2.5° and 10° eccentricity. Compared with photopic conditions, RA was larger, with the difference between RA and the Goldmann III stimulus (0.43°) being minimised. RGC number underlying RA was also higher than reported for photopic conditions (median 70 cells, IQR 36-93), with no significant difference being observed across test locations. Ricco's area and the number of RGCs underlying RA do not vary significantly across the central visual field in mesopic conditions. However, RA is larger and more similar to the standard perimetric Goldmann III stimulus under mesopic compared with photopic adaptation conditions. Further work is required to determine if compensatory enlargements in RA occur in age-related macular degeneration, to establish the optimal stimulus parameters for AMD-specific microperimetry.

Study on the Relationship between Resistivity and the Physical Properties of Seafloor Sediments Based on the Deep Neural Learning Algorithm

The occurrence of deep-sea geohazards is accompanied by dynamic changes in the physical properties of seafloor sediments. Therefore, studying the physical properties is helpful for monitoring and early warnings of deep-sea geohazards. Existing physical property inversion methods have problems regarding the poor inversion accuracy and limited application scope. To address these issues, we establish a deep learning model between the resistivity of seafloor sediment and its density, water content, and porosity. Compared with empirical formulas, the deep learning model has the advantages of a more concentrated prediction range and a higher prediction accuracy. This algorithm was applied to invert the spatial distribution characteristics and temporal variation of the seafloor sediment density, water content, and porosity in the South China Sea hydrate test area for 12 days. The study reveals that the dynamic changes in the physical properties of seafloor sediments in the South China Sea hydrate zone exhibit obvious stratification characteristics. The dynamic changes in the physical properties of seafloor sediments are mainly observed at depths of 0–0.9 m below the seafloor, and the sediment properties remain stable at depths of 0.9–1.8 m below the seafloor. This study achieves the monitoring and early warning of dynamic changes in the physical properties of seafloor sediments and provides a guarantee for the safe construction of marine engineering.

Spatial variation of feature density in multiscale topographic data

Digital topographic maps are created in a series of scales from large to small, and the underlying spatial data is commonly organized as a multiscale database consisting of several levels of detail (LoDs). Spatial density of features (or spatial objects) in such database varies both between LoDs (coarser levels are less densely populated with features) and within each LoD (feature density changes over the area). While the former type of density variation is caused by generalization, the latter one is mainly conditioned by geographic location and its properties, such as landscape complexity or fraction of urban areas. Since topographic database LoDs are derived using different data sources and generalization techniques, there is a need for a method that can help with automated evaluation of resulting feature density in terms of its appropriateness for the specified location and level of detail. This paper provides such method by uncovering dependencies between the location properties and the density of spatial data in multiscale topographic database. Changes in feature density are modeled as a function of spatial (landscape complexity and terrain ruggedness) and non-spatial (land cover types ratio) measures estimated via independent data sources. Resulting model predicts how much higher or lower is the expected spatial density of features over the area in comparison to the average density for the LoD. This information can be used further to assess the fitness of the data to the desired level of detail of the topographic map.