Local Map Research Articles

Annotated checklist of louse flies (Diptera, Hippoboscidae) occurring in Estonia

Previous data on Estonian louse flies (Diptera, Hippoboscidae) are dispersed across various, mainly local scientific articles and popular science writings, making them inaccessible to a broader interna‑ tional audience. No comprehensive species list or reviews are currently available. This study consolidates data from published sources, insect collections, and newly collected specimens to provide a comprehen‑ sive species list, supplemented with voucher specimen information. In total, nine species are confirmed to occur in Estonia, including two species, Ornithomya chloropus (Bergroth, 1901) and O. fringillina Curtis, 1836, recorded for the first time. Two species associated with livestock, Hippobosca equina Linnaeus, 1758 and Melophagus ovinus (Linnaeus, 1758), have been rarely encountered and are apparently nearing local extinction due to the increased use of effective insecticides and a decline in farming. Collection locality maps and habitus photographs from collected specimens are provided for all nine Estonian species.

Impact of Surface Finishing on Ti6Al4V Voronoi Additively Manufactured Structures: Morphology, Dimensional Deviation, and Mechanical Behavior

Additively manufactured medical devices require proper surface finishing before their use to remove partially adhered particles and provide adequate surface roughness. The literature widely investigates regular lattice structures—mainly scaffolds with small pores to enhance osseointegration; however, only a few studies have addressed the impact of surface finishing on the dimensional deviation and the global and local mechanical responses of lattice samples. Therefore, the current research investigates the impact of biomedical surface finishing (i.e., corundum sandblasting and zirconia sandblasting) on Voronoi lattice structures produced by laser powder bed fusion (LPBF) with large pores and different thicknesses on the surface morphology and global and local mechanical behaviors. MicroCT and SEM are performed for the assessment of dimensional mismatch and surface evaluation. The mechanical properties are investigated with 2D digital image correlation (DIC) in quasi-static compression tests to estimate the impact of surface finishes on local maps of strain. In the quasi-static tests, both the global mechanical performances, as expected, and local 2D DIC strain maps were mainly affected by the strut thickness, and the impact of different surface finishings was irrelevant; on the contrary, different surface finishing processes led to differences in the dimensional deviation depending on the strut thickness. These results are relevant for designing lattice structures with thin struts that are integrated into medical prostheses that undergo AM.

Contour and texture preservation underwater image restoration via low-rank regularizations

Due to the wavelength-dependent absorption and scattering, underwater images are often degraded by color distortion, haze, and low contrast. Despite the great advancements achieved in improving the quality of underwater image, the loss of contour and texture details in the restored results remains a major obstacle for subsequent high-level visual tasks. To this end, we develop a novel variational model, including one data term and two fidelity terms, for underwater image restoration. Technically, according to Retinex theory, we first extend the traditional underwater image formation (UIF) model by decomposing the total radiance into the reflectance component and illumination component. Based on the extended UIF model, two low-rank penalty regularization terms are designed to constrain the gradients of reflectance and illumination. Furthermore, we innovatively incorporate the weighted fusion bright-dark channel algorithm and the fusion upper-middle channel prior algorithm into the proposed variational model for estimating the local background light (ambient illumination) and transmission map, respectively. Simultaneously, based on the alternating direction multiplier method (ADMM), we develop a fast optimization algorithm to speed up the iterative process. Extensive experiments demonstrate that the proposed method is effective in removing haze, enhancing contrast and sharpness, as well as preserving the image contour and texture details. Comprehensive comparisons on two large-scale underwater image datasets further validate the superiority of our method against several state-of-the-art methods in both qualitative and quantitative evaluations. The code of the proposed method will be available soon.

Dolomite, quartzite, and sand indices defined for PRISMA hyperspectral data. Application to the Tamlalet inlier (Eastern High Atlas, Morocco)

The present work discusses the development of three novel spectral indices for PRISMA data. The Hyperspectral Dolomite Index (HDI) using B2320nm and B2349nm bands, the Hyperspectral Sand Index (HSI) based on the visible B515nm and B596nm bands, and the Hyperspectral Quartzite Index (HQI) using a combination of Relative Band Depths in B2167nm and B2206nm bands. The outputs of the three indices are grayscale images, where the brightest pixels represent the indices target. Applying HDI on PRISMA image of Tamlalet inlier (Moroccan Eastern High Atlas) led to discriminate the dolomites from lacustrine limestones and bare soils. HDI also suggests rectifying the local geological map by replacing limestones with dolomites in Jbel Ain Chair. HQI highlights quartz-rich rocks and provides better results than ASTER TIR indices. HSI can discriminate sand dunes from bare soils without being disturbed by vegetation. Dolomite, Quartzite, and Sand Hyperspectral indices show an overall accuracy of 91.2 %, 97.8 %, and 91.5 %, respectively. These indices could be adapted to other hyperspectral data having the required wavelengths.

Multipath Identification, User Localization, and Environment Mapping in Radio SLAM

Multipath Identification, User Localization, and Environment Mapping in Radio SLAM

Grazing-sliding bifurcation in a dry-friction oscillator on a moving belt under periodic excitation.

In this paper, we consider the grazing-sliding bifurcations in a dry-friction oscillator on a moving belt under periodic excitation. The system is a nonlinear piecewise smooth system defined in two zones whose analytical expressions of the solutions are not available. Thus, we obtain conditions of the existence of grazing-sliding orbits numerically by the shooting method. Then, we compute the lower and higher order approximations of the stroboscopic Poincaré map, respectively, near the grazing-sliding bifurcation point by the method of local zero-time discontinuity mapping. The results of computing the bifurcation diagrams obtained by the lower and higher order maps, respectively, are compared with those from direct simulations of the original system. We find that there are big differences between the lower order map and the original system, while the higher order map can effectively reduce such disagreements. By using the higher order map and numerical simulations, we find that the system undergoes very complicated dynamical behaviors near the grazing-sliding bifurcation point, such as period-adding cascades and chaos.

Local mapping of root orientation traits by X-ray micro-CT and 3d image analysis: A study case on carrot seedlings grown in simulated vs real weightlessness.

Root phenotyping is particularly challenging because of complexity and inaccessibility of root apparatus. Orientation is one of the most important architectural traits of roots and its characterization is generally addressed using multiple approaches often based on overall measurements which are difficult to correlate to plant specific physiological aspects and its genetic features. Hence, a 3D image analysis approach, based on the recent method of Straumit, is proposed in this study to obtain a local mapping of root angles. Proposed method was applied here on radicles of carrot seedlings grown in real weightlessness on the International Space Station (ISS) and on Earth simulated weightlessness by clinorotation. A reference experiment in 1g static condition on Earth was also performed. Radicles were imaged by X-ray micro-CT and two novel root orientation traits were defined: the "root angle to sowing plane" (RASP) providing accurate angle distributions for each analysed radicle and the "root orientation changes" (ROC) number. The parameters of the RASP distributions and the ROC values did not exhibit any significant difference in orientation between radicles grown under clinorotation and on the ISS. Only a slight thickening in root corners was found in simulated vs real weightlessness. Such results showed that a simple uniaxial clinostat can be an affordable analog in experimental studies reckoning on weightless radicles growth. The proposed local orientation mapping approach can be extended also to different root systems providing a contribution in the challenging task of phenotyping complex and important plant structures such as roots.

Intrinsic Universality in Automata Networks III: On Symmetry versus Asynchrony

An automata network is a finite assembly of interconnected entities endowed with a set of local maps defined over a common finite alphabet. These relationships are represented through an interaction graph. Together with the local functions, an assignment known as an update scheme directs the evolution of the network by updating specific subsets of entities at discrete time steps. Despite the scrutiny of interaction graphs and update schemes, their profound impact on automata network dynamics remains largely open. This work investigates the intricate interplay between these aspects, with a focus on how update schemes can counterbalance constraints stemming from symmetric local interactions. This paper is the third of a series about intrinsic universality, a notion that assesses both dynamical and computational complexity, encompassing transient behaviors, attractors, and prediction or reachability problems. We consider four update modes—parallel, block-sequential, local clocks, and general periodic— along with several families of symmetric signed conjunctive boolean networks defined by local constraints on signs. Our main result is to show a diagonal complexity leap in this two-dimensional landscape: the stronger the local constraints the higher the level of asynchrony required to obtain intrinsic universality or increase in complexity. We also show how in some cases asynchronism allows to simulate directed interactions from undirected ones with the same local rules.

Quaternion attention-based JND model for macrophotography image watermarking

With the advancement of imaging technology, macrophotography images (MPIs) have become a popular research topic. Unlike natural images, MPIs often feature sharp foregrounds and blurred backgrounds, leading to distinct perceptual characteristics in estimation. As the number of MPIs grows rapidly, concerns over image quality and security increase. Robust watermarking techniques have been introduced to address these challenges. Just Noticeable Difference (JND) has been widely used in quantization-based watermarking frameworks. However, existing JND models handle each image area with a single-level perceptual attention. Visual attention in Quaternion Discrete Wavelet Transform (QDWT), which can reflect the Multi-level perceptual attention feature. Therefore, we propose a new method called Quaternion Attention-based Just Noticeable Difference model for MPIs Watemarking (QAJnd-MW) for watermarking MPIs. This method uses visual attention mechanisms, recognizing that the HVS is more sensitive to attention regions. We generate a masking effect in the JND field. The input image undergoes QDWT to explore multi-scale features. The multi-scale feature maps, with multi-directional luminance and multi-channel color, help create local and global attention maps, which are fused to form the final attention map. Specifically, considering both attention-based masking effects, the quaternion attention-guided JND model is designed for a robust MPI watermarking framework, aiming to further improve MPI security. Extensive experiments on the MP2020 and Blur Detection datasets show that the proposed model significantly improves robustness against JPEG compression attacks, reducing the bit error rate (BER) by up to 12%. Additionally, the model performs well against other attacks, such as those in online social networks, with lower BER than current state-of-the-art techniques.

Disproportionate contributions of land cover and changes to ecosystem functions in Kazakhstan and Mongolia

Land use and land cover change (LULCC) have profoundly altered land surface properties and ecosystem functions, including carbon and water production. While mapping these changes from local to global scales has become more achievable due to advancements in earth observations and remote sensing, linking land cover changes to ecosystem functions remains challenging, especially at regional scale. Our study attempts to fill this gap by employing a computationally efficient method and two types of widely used high-resolution satellite images. We first investigated the contribution of landscape composition to ecosystem function by examining how land cover and proportion affected gross primary production (GPP) and evapotranspiration (ET) at six macro-landscapes in Mongolia and Kazakhstan. We hypothesized that both ecosystem and landscape GPP and ET are disproportionate to their composition and, therefore, changes in land cover will have asymmetrical influences on landscape functions. We leveraged a computational-friendly linear downscaling approach to align the coarse spatial resolution of MODIS (500 m) with a fine-grain and localized land cover map developed from Landsat (30 m) for six provinces in countries where intensive LULCC occurred in recent decades. By establishing two metrics—function to composition ratio (F/C) and function to changes in composition change (ΔF/ΔC)—we tested our hypothesis and evaluated the impact of land cover change on ecosystem functions within and among the landscapes. Our results show three major themes. (1) The five land cover types have signature downscaled ET and GPP that appears to vary between the two countries as well as within each country. (2) F/C of ET and GPP of forests is statistically greater than 1 (i.e., over-contributing), whereas F/C of grasslands and croplands is close to or slightly less than 1 (i.e., under-contribution). F/C of barrens is clearly lower than 1 but greater than zero. Specifically, a unit of forest generates 1.085 unit of ET and 1.123 unit of GPP, a unit of grassland generates 0.993 unit of ET and GPP, and a unit of cropland produces 0.987 unit of ET and 0.983 unit of GPP. The divergent F/C values among the land cover classes support the hypothesis that landscape function is disproportionate to its composition. (3) ΔET/ΔC and ΔGPP/ΔC of forests and croplands showed negative values, while grasslands and barrens showed positive values, indicating that converting a unit of forest to other land cover leads to a decrease in ET and GPP, while converting units of grassland or barren to other land cover classes will result in increased ET and GPP. This linear downscaling approach for calculating F/C and ΔF/ΔC is labor-saving and cost-effective for rapid assessment on the impact of land use land cover change on ecosystem functions.

CryoTEN: Efficiently Enhancing Cryo-EM Density Maps Using Transformers.

Cryogenic Electron Microscopy (cryo-EM) is a core experimental technique used to determine the structure of macromolecules such as proteins. However, the effectiveness of cryo-EM is often hindered by the noise and missing density values in cryo-EM density maps caused by experimental conditions such as low contrast and conformational heterogeneity. Although various global and local map sharpening techniques are widely employed to improve cryo-EM density maps, it is still challenging to efficiently improve their quality for building better protein structures from them. In this study, we introduce CryoTEN - a three-dimensional U-Net style transformer to improve cryo-EM maps effectively. CryoTEN is trained using a diverse set of 1,295 cryo-EM maps as inputs and their corresponding simulated maps generated from known protein structures as targets. An independent test set containing 150 maps is used to evaluate CryoTEN, and the results demonstrate that it can robustly enhance the quality of cryo-EM density maps. In addition, the automatic de novo protein structure modeling shows that the protein structures built from the density maps processed by CryoTEN have substantially better quality than those built from the original maps. Compared to the existing state-of-the-art deep learning methods for enhancing cryo-EM density maps, CryoTEN ranks second in improving the quality of density maps, while running > 10 times faster and requiring much less GPU memory than them. The source code and data is freely available at https://github.com/jianlin-cheng/cryoten.

Fine-mapping of a major QTL controlling plant height by BSA-seq and transcriptome sequencing in cotton.

GhSOT (GH_D05G3950) plays a negative role in regulating plant height development by modulating the GA signaling. Plant height is an important indicator affecting mechanical harvesting for cotton. Therefore, understanding the genes associated with the plant height is crucial for cotton breeding and production. In this study, we used bulk segregant analysis sequencing to identify a new quantitative trait locu (QTL) called qPH5.1, which is linked to plant height. Local QTL mapping using seven kompetitive allele-specific PCR(KASP) markers and linkage analysis successfully narrowed down qPH5.1 to ~ 0.34 Mb region harbored five candidate genes. Subsequently, RNA sequencing (RNA-seq) analysis and examination of expression patterns revealed that GhSOT exhibited the highest likelihood of being the candidate gene responsible for the plant height at this locus. Seven SNP site variations were identified in the GhSOT promoter between the two parents, and Luciferase experiments confirmed that the promoter of GhSOT from cz3 enhances downstream gene expression more effectively. Additionally, suppression of GhSOT in cz3 resulted in the restoration of plant height, further emphasizing the functional significance of this gene. Application of exogenous gibberellin acid (GA) significantly restored plant height in cz3, as demonstrated by RNA-seq analysis and exogenous hormone treatment, which revealed alterations in genes associated with GA signaling pathways. These results reveal GhSOT is a key gene controlling plant height, which may affect plant height by regulating GA signaling.

On 2-local derivations of von Neumann algebras

Let A be a semi-finite factor von Neumann algebra. We prove that if a map δ : A → A satisfies that for any A , B ∈ A there is a linear derivation δ A , B : A → A such that δ ( A ) B + Aδ ( B ) = δ A , B ( AB ) , then δ is a linear derivation. It is a positive answer to the problem on semi-finite factor von Neumann algebra posed by Molnár in the paper [A new look at local maps on algebraic structures of matrices and operators, New York J Math 28 (2022)].

A Texture-Considerate Convolutional Neural Network Approach for Color Consistency in Remote Sensing Imagery

Remote sensing allows us to conduct large-scale scientific studies that require extensive mapping and the amalgamation of numerous images. However, owing to variations in radiation, atmospheric conditions, sensor perspectives, and land cover, significant color discrepancies often arise between different images, necessitating color consistency adjustments for effective image mosaicking and applications. Existing methods for color consistency adjustment in remote sensing images struggle with complex one-to-many nonlinear color-mapping relationships, often resulting in texture distortions. To address these challenges, this study proposes a convolutional neural network-based color consistency method for remote sensing cartography that considers both global and local color mapping and texture mapping constrained by the source domain. This method effectively handles complex color-mapping relationships while minimizing texture distortions in the target image. Comparative experiments on remote sensing images from different times, sensors, and resolutions demonstrated that our method achieved superior color consistency, preserved fine texture details, and provided visually appealing outcomes, assisting in generating large-area data products.

Weakly Supervised Temporal Action Localization With Bidirectional Semantic Consistency Constraint.

Weakly supervised temporal action localization (WTAL) aims to classify and localize temporal boundaries of actions for the video, given only video-level category labels in the training datasets. Due to the lack of boundary information during training, existing approaches formulate WTAL as a classification problem, i.e., generating the temporal class activation map (T-CAM) for localization. However, with only classification loss, the model would be suboptimized, i.e., the action-related scenes are enough to distinguish different class labels. Regarding other actions in the action-related scene (i.e., the scene same as positive actions) as co-scene actions, this suboptimized model would misclassify the co-scene actions as positive actions. To address this misclassification, we propose a simple yet efficient method, named bidirectional semantic consistency constraint (Bi-SCC), to discriminate the positive actions from co-scene actions. The proposed Bi-SCC first adopts a temporal context augmentation to generate an augmented video that breaks the correlation between positive actions and their co-scene actions in the inter-video. Then, a semantic consistency constraint (SCC) is used to enforce the predictions of the original video and augmented video to be consistent, hence suppressing the co-scene actions. However, we find that this augmented video would destroy the original temporal context. Simply applying the consistency constraint would affect the completeness of localized positive actions. Hence, we boost the SCC in a bidirectional way to suppress co-scene actions while ensuring the integrity of positive actions, by cross-supervising the original and augmented videos. Finally, our proposed Bi-SCC can be applied to current WTAL approaches and improve their performance. Experimental results show that our approach outperforms the state-of-the-art methods on THUMOS14 and ActivityNet. The code is available at https://github.com/lgzlIlIlI/BiSCC.

Monocular BEV Perception of Road Scenes via Front-to-Top View Projection.

HD map reconstruction is crucial for autonomous driving. LiDAR-based methods are limited due to expensive sensors and time-consuming computation. Camera-based methods usually need to perform road segmentation and view transformation separately, which often causes distortion and missing content. To push the limits of the technology, we present a novel framework that reconstructs a local map formed by road layout and vehicle occupancy in the bird's-eye view given a front-view monocular image only. We propose a front-to-top view projection (FTVP) module, which takes the constraint of cycle consistency between views into account and makes full use of their correlation to strengthen the view transformation and scene understanding. In addition, we apply multi-scale FTVP modules to propagate the rich spatial information of low-level features to mitigate spatial deviation of the predicted object location. Experiments on public benchmarks show that our method achieves various tasks on road layout estimation, vehicle occupancy estimation, and multi-class semantic estimation, at a performance level comparable to the state-of-the-arts, while maintaining superior efficiency.

Understanding the spatial pattern and structural characteristics of cities in late feudal China: evidence from the local chronicle maps of the qing dynasty (1644–1911)

ABSTRACT Our study analyzes the spatial pattern and structural characteristics of cities in late feudal China based on multiple correlation and geographic information system spatial analysis, using 58 local Chinese chronicle maps of Jiangsu in the Qing Dynasty as research material. The elements in the city map were dominated by the types of official buildings, transportation facilities, and religious buildings. The urban spatial pattern can be classified into four types, such as extraverted and introverted, with each type having an aggregated spatial distribution and a gradual introverted orientation in time. The urban spatial structure can also be divided into four types: traditional, axial, random, and composite. Spatial distribution of each type is relatively stable, with little change over time. The geographic environment and the traditional concept of city building are the basic reasons for the formation of the spatial pattern and structure. The flood disaster, commercial and military factors contribute to the diverse structures. Our study demonstrates the feasibility of quantifying the ancient Chinese chronicles’ city maps. The findings have important value for contemporary ancient city restoration and shaping urban characteristics.

Strain localisation and grain boundary-mediated deformation in pure titanium at low and high temperatures: In-situ optical microscopy and digital image correlation

Heterogeneous deformation occurs between grains in polycrystalline α-titanium. Understanding the role of temperature in local deformation is essential for its applications in extreme environments such as cryo- or high-temperature, but the underlying mechanism still remains elusive. Here we report a study of grain-scale deformation behaviour in CP-Ti plate at the temperature range from −60 °C to 280 °C. The full-field strain measurements were conducted on the tensile samples loaded parallel (RD) and transverse (TD) to the rolling direction, using in-situ optical microscopy and digital image correlation (OM-DIC). The DIC local strain maps were coupled with scanning electron microscopy and electron backscatter diffraction analysis. The grain boundary sliding and slip transfer occurred depending on the geometric relationship (i.e., deformation compatibility) between adjacent grains at 20 °C, and a micro-crack was observed at the {101‾1} twist boundary. The strain was recovered in the grains in the RD sample favourable for slip, whilst more accumulated in the grains in TD sample unfavourable for slip at 280 °C. The plasticity of grains differs with decreasing temperature to −40 °C, resulting in the presence of soft/hard grain pairs. The strong strain localisation between the soft and hard grains led to the cracking along the GBs (RD) and cross the grains (TD). Interestingly, the cracking was significantly reduced with decreasing temperature to −60 °C due probably to the temperature dependence of the plasticity of grains. The strain-hardening behaviour of α-Ti polycrystals was significantly affected by the temperature and crystal orientation dependence of grain-scale deformation mechanism.

BA-CLM: A Globally Consistent 3D LiDAR Mapping Based on Bundle Adjustment Cost Factors.

Constructing a globally consistent high-precision map is essential for the application of mobile robots. Existing optimization-based mapping methods typically constrain robot states in pose space during the graph optimization process, without directly optimizing the structure of the scene, thereby causing the map to be inconsistent. To address the above issues, this paper presents a three-dimensional (3D) LiDAR mapping framework (i.e., BA-CLM) based on LiDAR bundle adjustment (LBA) cost factors. We propose a multivariate LBA cost factor, which is built from a multi-resolution voxel map, to uniformly constrain the robot poses within a submap. The framework proposed in this paper applies the LBA cost factors for both local and global map optimization. Experimental results on several public 3D LiDAR datasets and a self-collected 32-line LiDAR dataset demonstrate that the proposed method achieves accurate trajectory estimation and consistent mapping.

Local Non Abelian Class Field Theory

The “local class field theory”, which can be defined as the description of the extensions of a given local field K in terms of the algebraic and analytic objects depending ony on the base K is one of the central problems of modern number theory. The theory developed for the abelian extensions, around the fundamental works of Artin and Hasse in the first quarter of the 20th century. It is natural to ask if one could construct this theory including the non-abelian extensions of the base field. There are two approches to this problem. One approach is based on the ideas of Langlands, and the other on Koch. Koch’s method was later generalized by Fesenko and Koch-de Shalit for some non-abelian extensions of the base field. On the other hand, Ikeda and Serbest extended Fesenko’s works to construct a non-abelian local class field theory. But there is a restriction for the base field K. In this study, we extended Ikeda-Serbest’s construction of the local reciprocity map for a certain local field to any local field. Also we have shown that the extended map satisfies the certain functoriality and ramification theoretic properties.