Patch Size Research Articles

Biometry study of foveal isoplanatic patch variation for adaptive optics retinal imaging.

The change in ocular wavefront aberrations with visual angle determines the isoplanatic patch, defined as the largest field of view over which diffraction-limited retinal imaging can be achieved. Here, we study how the isoplanatic patch at the foveal center varies across 32 schematic eyes, each individualized with optical biometry estimates of corneal and crystalline lens surface topography, assuming a homogeneous refractive index for the crystalline lens. The foveal isoplanatic patches were calculated using real ray tracing through 2, 4, 6 and 8 mm pupil diameters for wavelengths of 400-1200 nm, simulating five adaptive optics (AO) strategies. Three of these strategies, used in flood illumination, point-scanning, and line-scanning ophthalmoscopes, apply the same wavefront correction across the entire field of view, resulting in almost identical isoplanatic patches. Two time-division multiplexing (TDM) strategies are proposed to increase the isoplanatic patch of AO scanning ophthalmoscopes through field-varying wavefront correction. Results revealed substantial variation in isoplanatic patch size across eyes (40-500%), indicating that the field of view in AO ophthalmoscopes should be adjusted for each eye. The median isoplanatic patch size decreases with increasing pupil diameter, coarsely following a power law. No statistically significant correlations were found between isoplanatic patch size and axial length. The foveal isoplanatic patch increases linearly with wavelength, primarily due to its wavelength-dependent definition (wavefront root-mean-squared, RMS <λ/14), rather than aberration chromatism. Additionally, ray tracing reveals that in strongly ametropic eyes, induced aberrations can result in wavefront RMS errors as large as λ/3 for an 8-mm pupil, with implications for wavefront sensing, open-loop ophthalmic AO, spectacle prescription and refractive surgery.

Decoupling foreground and background with Siamese ViT networks for weakly-supervised semantic segmentation

Due to the coarse granularity of information extraction in image-level annotation-based weakly supervised semantic segmentation algorithms, there exists a significant gap between the generated pseudo-labels and the real pixel-level labels. In this paper, we propose the DeFB-SV framework, which consists of a dual-branch Siamese network structure. This framework separates the foreground and background of images by generating unified resolution and mixed resolution class activation maps, which are then fused to obtain pseudo-labels. The mixed-resolution class activation maps are produced by a new mixed-resolution patch partition method, where we introduce a semantically heuristic patch scorer to divide the image into patches of different sizes based on semantics. Additionally, a novel multi-confidence region division mechanism is proposed to enable the adaptive extraction of the effective parts of pseudo-labels, further enhancing the accuracy of weakly supervised semantic segmentation algorithms. The proposed semantic segmentation framework, DeFB-SV, is evaluated on the PASCAL VOC 2012 and MS COCO 2014 datasets, demonstrating comparable segmentation performance with state-of-the-art methods.

Multiscale spatial analysis of two plant–insect interactions: effects of landscape, resource distribution, and other insects

ContextBiotic resource exploitation is a critical determinant of species’ distributions. However, quantifying resource exploitation patterns through space and time can be difficult, complicating their incorporation in spatial ecology studies. Therefore, understanding the local drivers of spatial patterns of resource exploitation may contribute to better large-scale species distribution models.ObjectivesWe investigated (1) how the resource exploitation patterns of two trophic interactions (plant–insect) are explained by insect behaviour, resource aggregation, and potential insect-insect interactions. We also analyzed how (2) resource patch size and (3) resource accessibility in a heterogeneous landscape affected host exploitation patterns.MethodsWe quantified nectar robbing by insects in the genus Bombus (bumblebees) and seed predation by Brachypterolus vestitus larvae (Antirrhinum beetle) on Antirrhinum majus L. (wild snapdragons) in the Pyrenees Mountains, Catalonia, Spain. We tested hypotheses about resource exploitation by integrating spatial analyses at multiple scales.ResultsBoth trophic interactions were aggregated, explained by the aggregation of their resource. At some scales, nectar robbing is more aggregated than the resource. Trophic interaction abundance is proportional to resource patch size, following the ideal free distribution model. Landscape features do not explain the locations exploited. Nectar robbing and seed predation occur together more often than expected.ConclusionsOur findings suggest that multiple biotic and ecological spatial factors may simultaneously affect resource exploitation at a local scale. These findings should be considered when developing agricultural projects, management plans and conservation policies.

Patterns of early post-disturbance reorganization in Central European forests.

Disturbances catalyse change in forest ecosystems, and a climate-driven increase in disturbance activity could accelerate forest reorganization. Here, we studied post-disturbance forests after the biggest pulse of tree mortality in Central Europe in at least 170 years, caused by drought and bark beetle (Scolytinae) outbreaks in 2018-2020. Our objectives were to characterize the early state of tree regeneration after mortality, quantify patterns of reorganization relative to undisturbed reference conditions and assess how management and patch size affect forest reorganization after disturbance. We surveyed 1244 plots in 120 patches under managed (salvage-logged, often planted) and unmanaged (deadwood remaining on site, no planting) conditions in Germany. We found that regeneration density on disturbed sites was high (median 11 897 stems ha-1), resulting from a cohort of advance regeneration. Disturbances were strong drivers of change, with indications for resilience on only 36.3% of patches. Reassembly (i.e. a change in species composition) was the dominant pattern of reorganization (61.5%), and Picea abies forests changed most strongly. Post-disturbance management facilitated forest change, particularly promoting a change in species composition. The strength of reorganization increased with patch size. We conclude that the recent wave of tree mortality will likely accelerate forest change in Central Europe.

Microneedling and 5-Fluorouracil in Treating Stable Vitiligo in Hitherto Unstudied High Prevalence Population

Abstract Background: Vitiligo, affecting 0.25% in India (&gt;1% in Jharkhand), stigmatises and devastates self-esteem/relationships causing depression. Apart from medical treatment, surgical procedures like applying 5-fluorouracil after microneedling are to be confirmed in unstudied populations and across time periods. An interventional study was conducted among out-patients of a tertiary hospital in a high-prevalence population wherein earlier attempts were not conducted. Aims/Objectives: To assess the effect of microneedling and applying 5% 5-fluorouracil on stable vitiligo patches. Methods and Materials: Microneedling and topical application of 5-fluorouracil was planned on 30 subjects of 10–50 age-groups with stable vitiligo, from September 2019 to September 2021 every 15 days for 12 visits. Age, gender, site, size/stability of vitiligo patches, leukotrichia and vitiligo family history were studied. Repigmentation (overall and variable-wise) was measured at each visit using 76–100% (excellent), 51–75% (very good), 25 to 50% (good) and &lt;25% (poor). Data was analysed with the Chi-square test or Standard Error of Difference between two proportions. Results: Under COVID restrictions (2020–2021), sample coverage was 77% (23/30) comprising 13 females and 10 males. Visits varied for each subject totalling 185 visits out of an expected 276 (67%). Significantly, 3 (13%) achieved excellent repigmentation, 10 (43%) very good, 8 (35%) good and only 2 (9%) poor repigmentation. Cumulatively, 13 (56%) attained excellent/very good repigmentation and 21 (91%) had excellent/very good/good repigmentation. Repigmentation ranged from 10% to 100% among 23 subjects, averaging 54% in average 8 visits (4 months). Repigmentation was equally achieved irrespective of age, gender, site, size and stability of the vitiliginous patch, presence/absence of leukotrichia and family history of vitiligo. Manageable pain (100%), itching (4%) and hyperpigmentation 43%, were side effects. Conclusion: Cumulative 91% (excellent/very good/good) repigmentation despite COVID-19 in the study period, and its comparability with other studies, strengthens evidence that microneedling and 5% 5-fluorouracil is effective in treating stable vitiligo in a high prevalence population.

VT-VT: a slip detection model for transformer-based visual-tactile fusion

Slip detection plays a crucial role in robotic operations and has received increasing attention in the field of robotics. We introduced a slip detection model called VT-VT, based on the fusion of vision and touch using a transformer architecture. The model leverages the advantages of a 'divided spatial-temporal attention' mechanism, capturing global contextual information more effectively and exhibiting high sensitivity to potential temporal features during the slipping process. To validate the effectiveness of VT-VT, we conducted experiments on a public slip detection dataset, achieving a test accuracy of up to 90.52%, significantly outperforming a convolutional neural network–long short-term memory model combined with different feature extraction networks. Furthermore, this study revealed the impact of different patch size values, different modal perception modes, and varying lighting conditions on the performance of the VT-VT model. Moreover, we analyzed the real-time capabilities of the VT-VT model.

Exploring resource patch occupancy: patch size, but not connectivity, explains the abundance of spider kleptoparasites in golden orb webs

Exploring resource patch occupancy: patch size, but not connectivity, explains the abundance of spider kleptoparasites in golden orb webs

Data-driven prediction of wind pressure on low-rise buildings in complex heterogeneous terrains

This study presents a data-driven methodology for predicting the pressure coefficient statistics on the windward wall, roof, and leeward wall of low-rise buildings situated downwind of complex heterogeneous terrains. Two types of artificial neural network models were developed: the empirical parameter-based ANN (PANN) and the morphology-based ANN (MANN). Pressure data from wind tunnel tests on the Wind Engineering Research Field Laboratory (WERFL) building model (building height H = 4 m) in complex heterogeneous terrain were used to develop the ANN models. These models were evaluated against a non-linear fitted model to assess their predictive performances. PANN and MANN demonstrated superior performance in capturing the effects of terrain complexity on the mean (Cp,mean) and the root-mean-square (Cp,RMS) wind pressure coefficients for the windward wall, roof, and leeward wall. Optimal prediction was achieved with a terrain patch size of W × L = 4 × 2, equating to a full-scale area of approximately 72 m × 23 m. This suggests that the morphology within approximately 100 m × 50 m (25H× 12.5H) in front of a low-rise building has the greatest correlation with the wind pressure coefficient. Despite lower R2 values for max Cp,RMS on the leeward wall across all models, both PANN and MANN showed promising accuracy for the six outputs studied. Moreover, a global sensitivity analysis confirmed the impact of terrain roughness and complexity on the prediction models particularly on max Cp,RMS, and underscored the dominance of effective roughness length z0,eff and the coefficient of variation of roughness length COVz0 in influencing model outcomes.

Improving extraction of forest canopy height through reprocessing ICESat-2 ATLAS and GEDI data in sparsely forested plain regions

ABSTRACT Forest canopy height (FCH) is one of the most important variables for carbon stock estimation. While many studies have focused on extracting FCH from spaceborne LiDAR in regions with spatially continuous and large patch sizes of forested lands, limited research has addressed the challenges of FCH extraction in plain regions with sparse and fragmented forest distributions. In this study, we proposed innovative processing approaches to extract FCH from ICESat-2 photons and GEDI footprints in the plain regions of Anhui Province, China. Specifically, we proposed a sectional photon denoising method for processing ICESat-2 data and a geolocation error correction method for processing GEDI data. Airborne LiDAR data were used to validate the extracted FCH products across typical plain regions. The results demonstrated the effectiveness of the proposed methods in improving FCH extraction accuracy. Evaluation indicated that the directly extracted FCH products from ATL08 and GEDI L2A had Pearson’s correlation coefficients (r) of 0.6 and 0.93, respectively. After processing with the proposed methods, the 2019 FCH products from ICESat-2 exhibited r of 0.82 and relative root mean square error (rRMSE) of 31.11% based on 3,217 ICESat-2 segments, and the products from GEDI showed r of 0.96 and rRMSE of 18.35% based on 4,862 GEDI footprints. Further application of these methods to extract FCH products from GEDI and ICESat-2 for the years 2020, 2021, and 2022 indicated their promise for addressing sparse vegetation coverage in plain regions.

Adaptation of farmland mammalian specialist to urban life: Escape behavior of European hare along the urban-rural gradient

The European hare Lepus europaeus is an iconic but rapidly declining farmland specialist with recently confirmed populations in urban areas. However, their behavioral responses and adaptability to urbanization and life in human-dominated areas are fully unexplored. Here, using infrared cameras, we explored escape behavior (measured as the flight initiation distance) using 965 hare observations in urban and farmland areas in the Czech Republic and Austria (Central Europe) and its association with habitat type, distance to the city center, patch size, season, hare age and initial behavior. We found that European hares adjusted their escape behavior to habitat type and escaped significantly earlier in farmland (rural) habitats than in urban habitats. However, escape distances of hares did not differ between farmland types with different degree of habitat heterogeneity. We also revealed that urban hares escaped earlier when located further from the city center or in a larger study patch. Moreover, adult hares escaped earlier than subadults and foraging individuals escaped earlier than resting hares but both only in rural areas. Our results support high behavioral adaptability of European hares to human-dominated urban areas.

Multi-Dimensional Landscape Connectivity Index for Prioritizing Forest Cover Change Scenarios: A Case Study of Southeast China

Predicting forest cover change (FCC) and screening development scenarios are crucial for ecological resilience. However, quantitative evaluations of prioritizing forest change scenarios are limited. Here, we took five shared socio-economic pathways (SSPs) representing potential global changes, namely SSP1: sustainability, SSP2: middle of the road, SSP3: regional rivalry, SSP4: inequality, and SSP5: fossil-fueled development, which were constructed by integrated assessment and climate models. We modeled them with the patch-generating land use simulation (PLUS) and constructed a multi-dimensional landscape connectivity index (MLCI) employing forest landscape connectivity (FLC) indices to assess forest development in Fujian Province, Southeast China. The MLCI visualized by radar charts was based on five metrics, including forest patch size (class area (CA), number (patch density (PD), isolation (landscape division index (DIVISION), aggregation (mean nearest-neighbor index (ENN_MN), and connectance index, (CONNECT). The results indicate that FC will remain above 61.4% until 2030, with growth observed in SSP1 and SSP4. Particularly, FC in SSP4 substantially increased, converted from cropland (1140.809 km2) and grassland (645.741 km2). SSP4 has the largest MLCI values and demonstrates significant enhancements in forest landscape integrity, with CA, ENN_MN and CONNECT increasing greatly. Our study offers valuable approaches to and insights into forest protection and restoration.

Patch spatial attributes and time to disturbance affect the emergence of source local populations within ephemeral habitats

Understanding the demography of local populations within ephemeral habitat patches is crucial for effective local (site-based) conservation management in spatially and temporally heterogeneous environments. Evidence suggests that species persisting in networks of ephemeral patches often exhibit source-sink dynamics, where certain local populations act as temporary sources at some time between initial colonization and patch disappearance due to disturbance. Here we present an individual-based demographic model inspired by Cabrera voles (Microtus cabrerae) in dynamic agricultural mosaics to test the hypothesis that the emergence of a source local population within an ephemeral habitat patch is largely driven by the combined effects of the patch spatial attributes (size, internal quality and connectivity to other hypothetical patches) and the time to disturbance (i.e. the patch lifespan). We focused on two key emergent demographic metrics quantifying the source-sink status of local populations based on their self-sustainability and potential contribution to other patches. We used sensitivity analyses to estimate the strength of linear associations between these metrics and the patch spatial attributes, and to quantify the main and interaction effects across different patch lifespans since initial colonization. Our model revealed that considerable spatial and temporal variation may emerge in local populations’ source-sink status based on differences in patch size, internal quality, connectivity, and lifespan. According to predictions, patch internal quality correlated positively with local population self-sustainability and potential contribution to other patches, though the strength of these relationships was mostly relevant only after about three vole generation times (ca. one year) since initial colonization, and only in combination with the positive effects of patch size and connectivity. Accordingly, results also supported the prediction that the emergence of a temporary source local population is conditional to the longevity of the habitat patch, with short patch lifespans (less than about three vole generation times) greatly limiting local population self-sustainability and potential contribution to other patches. While empirical testing is needed to confirm these findings, our study strengthens the view that local management efforts focusing on reducing or mitigating disturbance (e.g. severe droughts, human farming activities) at large and well-connected high-quality patches will likely promote the occurrence of temporary source local populations, which should be crucial for long-term species persistence over larger spatial scales.

Protected area creation and its limited effect on deforestation: Insights from the Kiziba-Baluba hunting domain (DR Congo)

The study examines the spatiotemporal dynamics of landscape anthropization in the Kiziba-Baluba Hunting Domain (KBHD), near Lubumbashi in southeastern Democratic Republic of Congo, facing increasing human threats. It assesses these dynamics from 1989 to 2023 using remote sensing, Geographic Information Systems (GIS), and landscape ecology principles. The results reveal a significant decrease in forest cover, declining from 70.33 % in 1989 to 26.22 % in 2023, with an annual deforestation rate of -1.84 %. This deforestation has led to the expansion of savannas (63.93 %), agriculture (5.76 %), and built-up and bare soil (0.93 %) through patch creation and aggregation. The level of landscape disturbance has increased sixfold over 34 years, from 0.42 in 1989 to 2.81 in 2023. The reduction in the size of the largest forest patch and increased spatial isolation show rising fragmentation and dissection, often followed by the attrition of residual patches. These findings highlight the inefficiency of current conservation measures in KBHD, indicating a need for restructuring management, redefining protected area boundaries, developing a suitable management plan, implementing reforestation programs, strengthening enforcement of environmental laws, and actively involving local communities.

Determining microbial metabolic limitation under the influence of moss patch size from soil extracellular enzyme stoichiometry

Determining microbial metabolic limitation under the influence of moss patch size from soil extracellular enzyme stoichiometry

Forest disturbance regimes and trends in continental Spain (1985–2023) using dense landsat time series

Forest disturbance regimes across biomes are being altered by interactive effects of global change. Establishing baselines for assessing change requires detailed quantitative data on past disturbance events, but such data are scarce and difficult to obtain over large spatial and temporal scales. The integration of remote sensing with dense time series analysis and cloud computing platforms is enhancing the ability to monitor historical disturbances, and especially non-stand replacing events along climatic gradients. Since the integration of such tools is still scarce in Mediterranean regions, here, we combine dense Landsat time series and the Continuous Change Detection and Classification - Spectral Mixture Analysis (CCDC-SMA) method to monitor forest disturbance in continental Spain from 1985 to 2023. We adapted the CCDC-SMA method for improved disturbance detection creating new spectral libraries representative of the study region, and quantified the year, month, severity, return interval, and type of disturbance (stand replacing, non-stand replacing) at a 30 m resolution. In addition, we characterised forest disturbance regimes and trends (patch size and severity, and frequency of events) of events larger than 0.5 ha at the national scale by biome (Mediterranean and temperate) and forest type (broadleaf, needleleaf and mixed). We quantified more than 2.9 million patches of disturbed forest, covering 4.6 Mha over the region and period studied. Forest disturbances were on average larger but less severe in the Mediterranean than in the temperate biome, and significantly larger and more severe in needleleaf than in mixed and broadleaf forests. Since the late 1980s, forest disturbances have decreased in size and severity while increasing in frequency across all biomes and forest types. These results have important implications as they confirm that disturbance regimes in continental Spain are changing and should therefore be considered in forest strategic planning for policy development and implementation.

Spatial patterning and species coexistence: A case study using concentric circular vegetation patches in saline land

Spatial patterns in plant community structures within stressed ecosystems have drawn much attention in the field of ecology. However, the mechanisms underlying spatial formation and its impact on species coexistence and diversity remain controversial. In this study, we investigated concentric circular vegetation patches in coastal saline land, and analysed the spatial patterning of plant communities and associated soil physicochemical properties. Thereafter, we tested how the soil conditioned by plant communities from different locations within the vegetation patches influence the species growth and inter-specific competition. Our results show soil salinity enlarges in a centrifugal manner in horizontal direction in all patches. Soil salinity decreased and species diversity increased along with the increase of patch size. In addition, we found significant shifts in both the composition of plant communities and in soil physicochemical properties from outer to center. The results indicate that the pioneer species Suaeda salsa facilitated the subsequent species. However Suaeda salsa was inhibited and became inferior competitor in the soil conditioned by the subsequent species. We infer that the less-visible spatial patterns of soil physicochemical properties at small scales create ecological niches for specialized species, allowing them to coexist but not mix. We suggest that a trade-off between tolerance to salt stress and competitive ability under ameliorated conditions may underlie mechanisms of pattern formation in small scale. Our findings lend support to the idea that soil stress constraints community assembly and triggers spatial patterns, which, in turn, buffer the stress on plant communities and enhance species diversity.

Land use history and landscape forest cover determine tropical forest recovery

Abstract To conserve biodiversity and combat climate change it is vital to restore forest ecosystems. Natural forest regrowth is a nature‐based solution to restore forests, but it has rarely been evaluated how this is affected by the combination of previous land use intensity and surrounding forest cover, and how this varies between the two main tropical forest types; dry and wet forests. Thirty‐three plots were established on abandoned agricultural fields in a dry (13 plots) and wet (20 plots) tropical forest in Mexico and monitored 3 years for the following tree community attributes: structure, diversity, regeneration mode, potential symbioses with N fixing bacteria and mycorrhizal fungi. Previous land use intensity was described using interviews, and landscape forest cover and fragmentation within a 1000 m radius surrounding the plots were quantified using satellite images. Variable importance analyses indicated that land use intensity was more important than forest cover and fragmentation for the state of the tree community attributes after 3 years. This suggests that previous land use impacts the start of succession and leaves important legacies on the vegetation. Land use intensity, forest cover and fragmentation were equally important in determining the change in tree community attributes over time, indicating that both management practices and dispersal shape subsequently community assembly. A higher land use intensity decreases tree richness recovery, while size of the largest forest patch decreases tree density and connectivity of these patches increases tree density. The dry forest had a faster increase in tree density recovery compared to the wet forest through a high initial resprouting capacity and abiotically dispersed trees. Synthesis and applications: Both a higher land use intensity and fragmented forest landscape decreases the speed of forest recovery, indicating that human actions and landscape transformation shape the course of succession. Restoration in fragmented forest landscapes through natural regeneration is more suitable in areas with low previous land use intensity, higher forest connectivity and abiotically dispersed species. Effective restoration should therefore consider both land use history and landscape forest cover and be tailored to local socio‐ecological conditions.

Direct measurement of self-diffusiophoretic force generated by active colloids of different patch coverage using optical tweezers

Hypothesis: Synthetic micro/nanomotors are gaining extensive attention for various biomedical applications (especially in drug delivery) due to their ability to mimic the motion of biological micro/nanoscale swimmers. The feasibility of these applications relies on tight control of propulsion speed, direction, and type of motion (translation, circular, etc.) along with the exerted self-propulsive force. We propose to exploit the variation of both self-propulsion speed and force of active colloids with different patch coverages (with and without supporting layer) for engineering diffusiophoretic micro/nanomotors.Experiments: The microswimmers were designed at various patch coverages (10°, 30°, and 90°) with (Ti/Pt) and without (Pt) an adhesion layer for the catalytic patch through glancing angle metal deposition (GLAD) technique. Mean-square displacement (MSD) analysis was performed to obtain the self-propulsion parameters like speed and angular speed. Using optical tweezers (OT), the self-propulsive force was measured from the force power spectral density.Findings: The findings of our experiments suggest the non-requirement of any adhesion layer preceding the catalyst deposition since the Pt 10° colloidal batch had the maximal self-propulsion speed (4.61±0.3μm/s) and force (345±57fN) for 5% w/v H2O2 fuel concentration. Moreover, the self-propulsion speed and force decreased with increasing patch size, contrary to theoretical estimates. Also, the self-propulsive force obtained from MSD is 2 to 4 times lower in magnitude than the OT based force values. We believe that the self-propelling motion of the micromotors is possibly hindered due to interactions with the surface of the quartz cuvette during the optical microscopic analysis. Further, the MSD is limited to the self-propulsive motion in two dimensions. On the other hand, OT based force measurement involve trapping the particles in the bulk of the solution entirely avoiding the particle–substrate interactions. Hence, OT based force measurements are better than the propulsion velocity based stokes drag force estimates. We believe that this study can lay the foundation in designing efficient micro/nanomotors for translational biomedical applications.

Land Cover Mapping in a Mangrove Ecosystem Using Hybrid Selective Kernel-Based Convolutional Neural Networks and Multi-Temporal Sentinel-2 Imagery

Mangrove ecosystems provide numerous ecological services and serve as vital habitats for a wide range of flora and fauna. Thus, accurate mapping and monitoring of relevant land covers in mangrove ecosystems are crucial for effective conservation and management efforts. In this study, we proposed a novel approach for mangrove ecosystem mapping using a Hybrid Selective Kernel-based Convolutional Neural Network (HSK-CNN) framework and multi-temporal Sentinel-2 imagery. A time series of the Normalized Difference Vegetation Index (NDVI) products derived from Sentinel-2 imagery was produced to capture the temporal behavior of land cover types in the dynamic ecosystem of the study area. The proposed algorithm integrated Selective Kernel-based feature extraction techniques to facilitate the effective learning and classification of multiple land cover types within the dynamic mangrove ecosystems. The model demonstrated a high Overall Accuracy (OA) of 94% in classifying eight land cover classes, including mangrove, tidal zone, water, mudflat, urban, and vegetation. The HSK-CNN demonstrated superior performance compared to other algorithms, including random forest (OA = 85%), XGBoost (OA = 87%), Three-Dimensional (3D)-DenseNet (OA = 90%), Two-Dimensional (2D)-CNN (OA = 91%), Multi-Layer Perceptron (MLP)-Mixer (OA = 92%), and Swin Transformer (OA = 93%). Additionally, it was observed that the structure of the network, such as the types of convolutional layers and patch sizes, affected the classification accuracy using the proposed model and, thus, the optimum scenarios and values of these parameters should be determined to obtain the highest possible classification accuracy. Overall, it was observed that the produced map could offer valuable insights into the distribution of different land cover types in the mangrove ecosystem, facilitating informed decision-making for conservation and sustainable management efforts.

Patency evaluation after venous resection and reconstruction with autologous peritoneum in laparoscopic pancreatectomy

BackgroundConcomitant venous resection during pancreatectomy for pancreatic space-occupying lesions with veinous involvement is increasingly performed to achieve oncological resection. This study aims to report a single-center experience in peritoneal patch graft for vascular reconstruction during laparoscopic pancreatectomy. MethodsA retrospective analysis of all 6 patients who underwent laparoscopic pancreatectomy as well as the venous reconstruction with autologous peritoneum graft were compared with the control group, 8 patients who received Laparoscopic pancreaticoduodenectomy with venous resection and primary anastomosis. Postsurgical complications and outcomes were evaluated. We specifically assessed the reconstructed venous patency ratio by Cross-sectional Area Algorithm which was based on post-surgical CT-Venograms, thereafter the overall patency ratio was compared with the control group. ResultsAll 6 patients underwent venous resection and reconstruction using peritoneum patches of appropriate size, which includes 5 cases of lateral patch repairing and 1 case of tubular repairing. There are no significant differences noticed in post-surgical complications and outcomes between the peritoneum graft group and the control group. However, most of the peritoneum graft cases showed stenosis or complete occlusion after surgery. Partial venous stenosis or complete occlusion did not cause abnormal liver function as newly formed venous collaterals were early detected and progressively robust. ConclusionsUse of peritoneal patch as a venous substitute during the laparoscopic pancreatectomy contains satisfied operability and safety. However, the post-surgical reconstructed venous patency was an issue that need to be noticed. Overall, the peritoneum repairing technique is a considerable choice that assisted the oncological resection in certain situations.