Structural Mapping Research Articles

Tectonometamorphic evolution of a subduction plate interface at the base of the Mirdita Ophiolite (Bajram Curri, northeastern Albania)

Abstract The Western Vardar ophiolite, a thrust sheet of oceanic crust and mantle obducted onto the Adriatic passive margin in the Late Jurassic, crops out along the entire Balkan Peninsula. The Mirdita Ophiolite forms the northern Albanian segment of this unit. In northeast Albania near Bajram Curri, a 200–700 m thick metamorphic sole is preserved at its base. The assembly of obducted mantle rocks and metamorphic sole constitutes a plate interface that formed during the intraoceanic subduction stage preceding obduction; we call this a fossil intraoceanic plate interface in this paper. This setting allows to study the interrelated tectonometamorphic evolution and rock-water interaction between the subducted and exhumed metamorphic sole and concomitant mantle wedge serpentinization in the overlying units. We combined detailed lithological and structural mapping with micro-scale analyses along this plate interface. Three tectonic units were distinguished. Mylonitic harzburgites overlie a tightly folded, tectonised subophiolitic mélange along a SE-dipping contact that defines the fossil intraoceanic plate interface. The tectonised subophiolitic mélange itself was separated into a structurally lower non-metamorphic broken formation and a higher metamorphic sole, separated by an isoclinally folded thrust. Within the metamorphic sole, the temperature and degree of deformation increase towards the structural top. Shear sense indicators in calcschists of the metamorphic sole show top to the west transport of the overriding units. All metamorphic sole lithologies were overprinted at lower greenschist-facies conditions, reflecting their exhumation from intraoceanic subduction. Corresponding microstructures indicate mineral growth at isotropic stresses, suggesting that deformation migrated into structurally lower, frontally accreted non-metamorphic units of the sub-ophiolitic mélange marking the start of obduction onto the passive Adriatic margin. Ongoing westward transport led to folding of the entire sub-ophiolitic succession. Harzburgites are more deformed towards the plate interface, forming a mylonitic fabric. There, harzburgites contain accessory Cr-rich spinel and the foliation is dissected by multiple generations of veins containing serpentine and magnetite. Vein density is highest along the plate interface and decreases up-section, suggesting that serpentinisation was triggered by devolatilisation reactions in the sediments of the metamorphic sole that were subducting below the harzburgites, and the upwards migration of volatiles into the overlying mantle wedge.

Large-angle Lorentz Four-dimensional scanning transmission electron microscopy for simultaneous local magnetization, strain and structure mapping

Small adjustments in atomic configurations can significantly impact the magnetic properties of matter. Strain, for instance, can alter magnetic anisotropy and enable fine-tuning of magnetism. However, the effects of these changes on nanoscale magnetism remain largely unexplored. In particular, when strain fluctuates at the nanoscale, directly linking structural changes with magnetic behavior poses a substantial challenge. Here, we develop an approach, LA-Ltz-4D-STEM, to map structural information and magnetic fields simultaneously at the nanoscale. This approach opens avenues for an in-depth study of structure-property correlations of magnetic materials at the nanoscale. We applied LA-Ltz-4D-STEM to image strain, atomic packing, and magnetic fields simultaneously in a deformed amorphous ferromagnet with complex strain variations at the nanoscale. An anomalous magnetic configuration near shear bands, which reside in a magnetostatically high-energy state, was observed. By performing pixel-to-pixel correlation of the different physical quantities across a large field of view, a critical aspect for investigating industrial ferromagnetic materials, the magnetic moments were classified into two distinct groups: one influenced by magnetoelastic coupling and the other oriented by competition with magnetostatic energy.

Generating synthetic CT images from unpaired head and neck CBCT images and validating the importance of detailed nasal cavity acquisition through simulations.

Computed tomography (CT) of the head and neck is crucial for diagnosing internal structures. The demand for substituting traditional CT with cone beam CT (CBCT) exists because of its cost-effectiveness and reduced radiation exposure. However, CBCT cannot accurately depict airway shapes owing to image noise. This study proposes a strategy utilizing a cycle-consistent generative adversarial network (cycleGAN) for denoising CBCT images with various loss functions and augmentation strategies, resulting in the generation of denoised synthetic CT (sCT) images. Furthermore, through a rule-based approach, we were able to automatically segment the upper airway in sCT images with high accuracy. Additionally, we conducted an analysis of the impact of finely segmented nasal cavities on airflow using computational fluid dynamics (CFD). We trained the cycleGAN model using various loss functions and compared the quality of the sCT images generated by each model. We improved the artifact removal performance by incorporating CT images with added Gaussian noise augmentation into the training dataset. We developed a rule-based automatic segmentation methodology using threshold and watershed algorithms to compare the accuracy of airway segmentation for noise-reduced sCT and original CBCT. Furthermore, we validated the significance of the nasal cavity by conducting CFD based on automatically segmented shapes obtained from sCT. The generated sCT images exhibited improved quality, with the mean absolute error decreasing from 161.60 to 100.54, peak signal-to-noise ratio increasing from 22.33 to 28.65, and structural similarity index map increasing from 0.617 to 0.865. Furthermore, by comparing the airway segmentation performances of CBCT and sCT using our proposed automatic rule-based algorithm, the Dice score improved from 0.849 to 0.960. Airway segmentation performance is closely associated with the accuracy of fluid dynamics simulations. Detailed airway segmentation is crucial for altering flow dynamics and contributes significantly to diagnostics. Our deep learning methodology enhances the image quality of CBCT to provide anatomical information to medical professionals and enables precise and accurate biomechanical analysis. This allows clinicians to obtain precise quantitative metrics and facilitates accurate assessment.

Deep learning-enhanced smart ground robotic system for automated structural damage inspection and mapping

Deep learning-enhanced smart ground robotic system for automated structural damage inspection and mapping

Reservoir characterization using seismic and well data, freeman field, Niger delta

This report details the workflow for the Reservoir Freeman field, encompassing 3D seismic interpretation and the development of a 3D static model through the comprehensive integration of available data. This includes 3D seismic data, well logs, deviation data, core samples, checkshot data, and production records. The study underscores the area's petroleum potential and presents petrophysical results from four wells to enhance reservoir characterization. Seismic interpretation identified five horizons and nineteen faults, mainly antithetic and basinward-dipping. The structural framework and time maps indicate a central structural high, suggestive of hydrocarbon accumulation zones. Petrophysical analysis delineated four key hydrocarbon reservoirs (A, B, C, and D) with average thicknesses of 27.14m, 22.00m, 18.07m, and 18.15m, respectively. Reservoir porosities ranged from 0.25 to 0.35, highlighting favourable storage capacity. Permeabilities between 1993.99mD and 3640.88mD indicate well-connected pore networks. Hydrocarbon saturation (SH) varied from 0.64 to 0.76, with movable hydrocarbon indices suggesting primarily movable oil. Volumetric analysis yielded STOOIP estimates of 38,118.36 bbl/acre (A), 36,319.85 bbl/acre (B), 25,379.47 bbl/acre (C), and 18,023.39 bbl/acre (D). These findings emphasize the potential of the Reservoir Freeman field for hydrocarbon development.

Droplet-based high-throughput 3D genome structure mapping of single cells with simultaneous transcriptomics

Single-cell three-dimensional (3D) genome techniques have advanced our understanding of cell-type-specific chromatin structures in complex tissues, yet current methodologies are limited in cell throughput. Here we introduce a high-throughput single-cell Hi-C (dscHi-C) approach and its transcriptome co-assay (dscHi-C-multiome) using droplet microfluidics. Using dscHi-C, we investigate chromatin structural changes during mouse brain aging by profiling 32,777 single cells across three developmental stages (3 months, 12 months, and 23 months), yielding a median of 78,220 unique contacts. Our results show that genes with significant structural changes are enriched in pathways related to metabolic process and morphology change in neurons, and innate immune response in glial cells, highlighting the role of 3D genome organization in physiological brain aging. Furthermore, our multi-omics joint assay, dscHi-C-multiome, enables precise cell type identification in the adult mouse brain and uncovers the intricate relationship between genome architecture and gene expression. Collectively, we developed the sensitive, high-throughput dscHi-C and its multi-omics derivative, dscHi-C-multiome, demonstrating their potential for large-scale cell atlas studies in development and disease.

Vertical structure observation from spaceborne lidar ICESat-2 in East China Sea.

Nowadays, spaceborne LiDAR technology, particularly ICESat-2, has become a transformative tool in marine environmental research. Unlike traditional passive optical remote sensing methods, ICESat-2 offers detailed vertical structure mapping of oceanic optical properties. Despite the potential of ICESat-2 for observing the optical vertical structure, its application in the East China Sea with complex hydrological conditions and dynamic ecosystems remains limited. In this study, we introduce an innovative methodology for retrieving the vertical structure of subsurface optical properties in the East China Sea using ICESat-2 spaceborne LiDAR observations. After preprocessing ICESat-2 ATL03 data, we employed a 4 km × 1 m bin with a 0.15 m depth step for sliding accumulation, allowing us to capture LiDAR signals at various water depths. Following deconvolution, we proposed a method to calculate the vertical profiles of the diffuse attenuation coefficient and the particulate backscatter coefficient, thereby obtaining their vertical distributions. Our retrieval results show a high degree of consistency with MODIS products and BGC-Argo data, particularly in clearer open waters. The optical parameters in the East China Sea exhibit a distinct spatial pattern, with elevated values in the western and northern regions and lower values in the eastern and southern regions. This distribution is largely attributed to the proximity of the northern laser track segments to land and the influence of terrestrial runoff from the Yangtze River on the western side of the East China Sea. The influx of suspended particles and nutrients in this region significantly affects the magnitude of optical parameters, resulting in higher root mean square errors (RMSE) compared to the eastern waters. Moreover, our analysis reveals notable differences in the vertical distribution of the diffuse attenuation coefficient and the particulate backscatter coefficient, reflecting varying concentrations of optically active components across different water layers. These findings validate the efficacy of ICESat-2 for retrieving the vertical structure of subsurface ocean optical properties, providing a robust foundation for understanding the dynamic changes within the East China Sea ecosystem.

Mapping of Agate-like Soil Cover Structures Based on a Multitemporal Soil Line Using Neural Network Filtering of Remote Sensing Data

The present study focuses on analysis of the soil cover structure (SCS, SCSs), which is the most detailed level of soil organization in space. The detail in which complex SCS can be studied is often insufficient, since until now it has not been possible to map it over large areas at scales larger than 1:10,000. To increase the detail in which SCS can be studied, the methods of identifying the bare soil surface (BSS) and averaging its multitemporal spectral characteristics were used, which opens up new possibilities for mapping complex SCS over large areas. New SCSs of leached chernozems (Luvic Chernic Phaeozem) were discovered, which can produce patterns on satellite images similar to sections of Timan agate—agate-like soil cover structures (ASCS, ASCSs). ASCSs are formed on Quaternary sediments of varying thickness from 0.3 to 6 m, underlain by carbonate and red sediments of the Permian period. The ASCS pattern is formed by ring-shaped stripes (rings) of different colors and brightness, which are determined by the carbonate and red-colored inclusions involved in the arable horizon. Eight soil varieties were identified to describe ASCSs during the study. According to the WRB, there are six main soil types, and according to the classification of Russian soils in 1977, there are four types. ASCSs were identified over large areas and soil maps of ASCSs were constructed using multitemporal spectral characteristics of the BSS in the form of multitemporal soil line coefficients. Neural networks were used to identify BSS on big remote sensing data. ASCSs have contrasting soil properties and contrasting fertility (productivity of agricultural crops). ASCS maps can serve as the basis for task maps of precision farming systems. Perhaps ASCSs are unique objects for the area of chernozem distribution, where in one soil profile there are rocks with an age from the first thousand years (Quaternary) to 250 million years (Permian). Chernozems are fertile, studied, mercilessly exploited, but sometimes they are simply beautiful—agate-like.

Analysis of Published Manuscripts on Napoleon Bonaparte

Napoleon Bonaparte stands out as one of the most important characters of the 19th century. This study was conducted to evaluate the manuscripts written for Napoleon Bonaparte. The number of publications, document types, the most attractive journals, the most chosen keywords, the most productive authors, the most cited articles, collaborative information about the studies, co-citation report, and the conceptual structure map for keywords used together were examined in this study. As a conclusion of this bibliometric study, it can be understood that the number of studies about Napoleon Bonaparte will increase. The results showed that overwhelming majority of the works on Bonaparte are single country publications. It can be suggested that multiple country publications can bring new scientific interpretations and reveal historical findings with the help of cooperation among researchers with different perspectives on the Napoleon Bonaparte who is one of the most influential character of the 19th century.

Structural determinants of peanut induced anaphylaxis.

Human monoclonal IgE antibodies recognizing peanut allergens have recently become available, but we lack a detailed understanding of how these IgEs target allergens. To determine the molecular details of the antibody-allergen interaction for a panel of clinically important human IgE monoclonal antibodies and to develop strategies to disrupt disease causing antibody-allergen interactions. We identified candidates from a panel of epitope binned human IgE monoclonals that recognize two important and homologous peanut allergens, Ara h 2 and Ara h 6. Crystal structures were determined revealing the interfaces (antigenic sites) of exemplars of five common IgE bins. Among the common antigenic sites on Ara h 2 and Ara h 6, two sites (A and B) are highly conserved between the allergens, explaining the cross reactivity of antibodies that recognize these sites. Three sites (C, D, and F) involve residues that are not conserved between the allergens. Of the five common sites, three Sites (B, C, and D) involve residues that are only near each other when the allergens are properly folded, such that these sites are conformational. Two additional sites (sites A and F) involve largely linear stretches of amino acids. Site F targeted antibody, 38B7, binds to a peptide sequence DPYSPOHS, in which hydroxylation of the last proline is critical for binding. This sequence is repeated two or three times depending on the Ara h 2 isoform, enabling 38B7 to induce anaphylaxis as a single monoclonal, without a second antibody. We have mutated key residues in each site and created a panel of hypoallergens, having reduced IgE mAb binding and lacking the ability to induce anaphylaxis in our murine model. We created a structural map of the IgE antibody response to the most important peanut allergen proteins to enable the design of new allergy immunotherapies and vaccines.

Design of Large-Span Beamforming Antenna Based on Beam Superposition and Structure Mapping

Design of Large-Span Beamforming Antenna Based on Beam Superposition and Structure Mapping

Predictive Methods and Probabilistic Mapping of Subcortical Brain Components in Fossil Carnivora.

Paleoneurology reconstructs the evolutionary history of nervous systems through direct observations from the fossil record and comparative data from extant species. Although this approach can provide direct evidence of phylogenetic links among species, it is constrained by the availability and quality of data that can be gleaned from the fossil record. Here, we sought to translate brain component relationships in a sample of extant Carnivora to make inferences about brain structure in fossil species. Using high resolution magnetic resonance imaging on extant canids and felids and 3D laser scanning on fossil Carnivora, spanning some 40 million years of evolution, we derived measurements for select brain components. From these primary data, predictive equations of cortical (gray matter mass, cortical thickness, and gyrification index) and subcortical structures (caudate nucleus, putamen, and external globus pallidus mass) were used to derive estimates for select fossil Carnivora. We found that regression equations based on both extant and simulation samples provided moderate to high predictability of subcortical masses for fossil Carnivora. We also found that using exploratory probabilistic mapping of subcortical structures in extant Carnivora, a reasonable prediction could be made of the 3D subcortical morphospace of fossil endocasts. These results identify allometric departures and establish adult species ranges in brain component size for fossil species. The integrative approach taken in this study may serve as a model to promote further dialog between neurobiologists working on extant Carnivora models and paleoneurologists describing the nervous system of fossils from this understudied group of mammals.

A Regional Structural Mapping Approach for Mineral Exploration: Application in the Southwestern Region of Burkina Faso

A Regional Structural Mapping Approach for Mineral Exploration: Application in the Southwestern Region of Burkina Faso

Tectono‐Magmatic Evolution of the Southern Reykjanes Ridge, North Atlantic, From ∼11 M.y. to Present

AbstractOur understanding of the geological evolution of mid‐ocean ridges in response to tectonic reconfigurations and associated mantle processes is hampered by a lack of exploration in off‐axis areas. A notable exception is the Reykjanes Ridge, where multibeam bathymetry, magnetics, and gravity surveys have been conducted up to ∼150 km from the ridge axis. Previous work shows that the ridge has undergone a major reorganization following changes in spreading direction, resulting in the progressive formation and then elimination of transform faults from north to south under the influence of the regional mantle melting anomaly. Notably, this process is incomplete near the southern termination of the ridge, providing a window into the processes of crustal accretion and segmentation prior to and immediately following this reorganization. Here, we employ remote‐predictive geological and structural mapping methods linked to chrono‐magnetic data to elucidate changes in segment morphology, magma supply, and structural fabrics along the southern ∼200 km of the ridge over the past ∼11 M.y. We identify two new fracture zones and three new non‐transform discontinuities, with elimination of transform motion occurring between ∼9.7 and 4.2 Ma, which is later than previously thought. Transform elimination coincides with rift propagation and the emergence of a new magmatically robust segment at ∼58°N at ∼9.7–8.2 Ma. This transition is also associated with a reorientation of seafloor fabric from dominantly N‐trending to NE‐trending, associated with the dissection of axial volcanic ridges by the oblique (NE‐trending) plate boundary, resulting in more crustal accretion to the North American plate overall.

The Adventure of Artificial Intelligence in Educational Research from the Past to the Present

This study aims to examine scientific studies on artificial intelligence (AI) in educational research from the past to the present, based on the Web of Science database. In this context, 1465 scientific articles containing AI in education from the past to the present were evaluated. Articles accessed from the WoS database were examined using a bibliometric analysis method according to productivity, network analyses, conceptual structure, and thematic map titles. Within the scope of productivity, authors, institutions, countries, citations within the scope of network analysis, authors, institutions, sources, and countries were included in the analysis. In addition, thematic changes over the years, word cloud, collaborations, conceptual formations, and thematic mapping were carried out based on keywords. In this context, 1465 scientific articles published by 3783 authors representing 86 countries were included in the research. According to the research findings, the number of studies and citations on AI in education has increased significantly, especially in the last five years. The Education University and The Chinese University of Hong Kong stand out as productive institutions. While China, England, and the USA stand out as the countries of responsible authors, Hwang, G. J., stands out as the author of network analysis, and the Computer Education journal stands out as the journal. As a thematic change in the studies, there has been an evolution towards new technological developments such as deep learning, machine learning, ChatGPT, chatbots, learning analytics, blockchain, and generative AI. According to the factor analysis conducted on the conceptual structure of AI-related studies in education, it was determined that it explained 48% of the total variability. According to the study findings, studies on AI applications in education should be enriched from a disciplinary perspective, and efficiency should be increased regarding their reflections on teaching.

VECTOR-LOGIC FAULT SIMULATION

Context. The technological trends of Design&Test computing for the IT industry and academic science are determined by the following directions: in-memory computing, immersive computing, AI computing, focused on energy saving and reduction of computing time when providing services. A mechanism for simulating faults as addresses on smart data structures is proposed, which eliminates the algorithm for simulating input test sets to obtain a test map for logic functionality. The proposed mechanism is focused on the service of SoC IP-cores under the control of the IEEE 1500 standard, which can be perceived positively by engineers in the EDA market. Objective. The purpose of the research is time- and energy-saving mechanisms for simulating malfunctions, such as addresses, by using read-write transactions of in-memory computing to build a test map of any functionality on smart data structures. Method. Smart data structures are represented by a logical vector and its derivatives in the form of truth tables and matrices. The test map is a matrix whose coordinates are determined by the combinations of all logical faults that are tested on the binary sets of the comprehensive test. The construction of the test map is focused on the architecture of in-memory computing based on read-write transactions, which makes the simulation mechanism economical in terms of simulation time and energy consumption due to the absence of a central processor. A logical vector as a single component of input data does not require synthesis into a technologically permitted structure of elements. Synthesis of smart data structures based on four matrix operations creates a fault test map like addresses for any logic. Results. Deductive matrix vectors are effectively used to model faults as addresses in digital structures of any configuration, including convergent branches and feedback loops. The resulting test map is used to find the minimum fault-checking test of the input variables. The proposed fault simulation mechanism technologically easily fits into the architecture of in-memory computing and uses only read-write transactions. The vector logic engine can also be used to test graph structures that are described by a truth table or a logical vector. The truth table addresses used for fault simulation are effectively used for processorless processing of large data in the in-memory computing architecture. Conclusions. Scientific novelty – a vector-logic in-memory computing mechanism for building a test map is proposed, characterized by the construction of intelligent data structures that reset the fault modeling algorithm. The proposed mechanism has no analogues in the design & test industry in terms of simplicity and predictability of data structure sizes and the absence of a test set modeling algorithm. The practical significance is determined by the application of the mechanism for testing logical functionalities of any complexity to solve verification tasks. Prospects of the research – increasing the object of diagnosis to the scheme, i.e. building a test map of the scheme logical structure.

A CRITICAL METAPHOR ANALYSIS OF ENVIRONMENTAL DISCOURSES IN THE PHILIPPINE SETTING

This research employed Critical Metaphor Analysis to examine the inaccuracies embedded in metaphors within the environmental discourses in the Philippines from a corpus of 30 documentary films. The study involved interviews with 5 science teachers and 5 senior high school students in the metaphor analyses. The pre-metaphor analysis level encompassed the discussions on pollution, climate change, biodiversity loss, and nature conservation. During the metaphor identification level, 35 conceptual metaphors containing inaccuracies were identified such as paradise, festival, treasure, refuge, landscape, society, patient, lungs, psychological disorder, sinking ship, waterworld, victims, battle, karma, last forest, symbols of freedom, burning, and simple solution domains. These are grouped into 12 conceptual keys such as ideal place, home, threat, interconnected system, living organism, monster, war, cause and effect, unrestricted movement, combustion, and simple solution source domains. At the metaphor interpretation phase, topics comprised conservation, preservation, and natural value; resource value and commodification of nature; waste and pollution; climate change and environmental degradation; and human influence and environmental ethics. The identified metaphors were characterized by orientational (5), ontological (17), and structural (13) mappings, with 23 metaphors conveying alarmist tones and 12 relational and hopeful tones. Purposes were found as ideological (9), empathetic (10), heuristic (7), and aesthetic (9). At the metaphor explanation level, ideologies such as human dominance, commodification, environmental ethics, sanctity of nature, and overwhelming burden were revealed reflecting modify (2), adapt (1), and depend (2) power dynamics. This study highlighted the cultural, ideological, and motivational underpinnings of metaphor usage in public media that can significantly shape public perception and environmental action. KEYWORDS: environmental discourses; documentary films; critical metaphor analysis; applied linguistics; Philippines

Insights on the structural framework of the Egyptian Eastern Desert derived from edge detectors of gravity data

Advanced geophysical techniques are used on Bouguer gravity data to unravel the structural complexity of the Eastern Desert (ED). Using methods such as tilt angle (TA), enhanced horizontal gradient amplitude (EHGA), lineament analysis, and 2D crustal modeling, we are able to differentiate between deep and shallow gravity sources and delineate the area’s geologic features. Using fast Fourier transform, positive and negative anomalies are identified. The positive anomalies are interpreted as uplifted block, anticline features, or intrusive occurrences of denser rocks, whereas the negative anomalies are interpreted as downfaulted blocks, providing crucial insights. Lineament analysis suggests that the predominant tectonic force that shaped the area is in the northwest direction. Integration of TA and EHGA reveals nuanced structural patterns. The constructed structural map indicates a network of uplifted and downfaulted blocks intersected by strike-slip faults with a northeast trend. The 2D crustal modeling illustrates the diverse composition of granitic and basaltic rocks, with a discernible thinning of the continental crust toward the Red Sea offshore area. This significantly advances the understanding of the ED’s geologic evolution, offering valuable insights into the tectonic processes and crustal dynamics.

Investigation of a Robust Blind Deconvolution Algorithm Using Extracted Structures in Light Microscopy Images of Salivary Glands: A Pilot Study

Although light microscopy (LM) images are widely used to observe various bodily tissues, including salivary glands, reaching a satisfactory spatial resolution in the final images remains a major challenge. The objective of this study was to model a robust blind deconvolution algorithm using the extracted structure and analyze its applicability to LM images. Given LM images of the salivary glands, the proposed robust blind deconvolution method performs non-blind deconvolution after estimating the structural map and kernel of each image. To demonstrate the usefulness of the proposed algorithm for LM images, the perceptual sharpness index (PSI), Blanchet’s sharpness index (BSI), and natural image quality evaluator (NIQE) were used as evaluation metrics. We demonstrated that when the proposed algorithm was applied to salivary gland LM images, the PSI and BSI were improved by 7.95% and 7.44%, respectively, compared with those of the conventional TV-based algorithm. When the proposed algorithm was applied to an LM image, we confirmed that the NIQE value was similar to that of a low-resolution image. In conclusion, the proposed robust blind deconvolution algorithm is highly applicable to salivary gland LM images, and we expect that further applications will become possible.

Verbal working memory and syntactic comprehension segregate into the dorsal and ventral streams, respectively.

Syntactic processing and verbal working memory are both essential components to sentence comprehension. Nonetheless, the separability of these systems in the brain remains unclear. To address this issue, we performed causal-inference analyses based on lesion and connectome network mapping using MRI and behavioural testing in two groups of individuals with chronic post-stroke aphasia. We employed a rhyme judgement task with heavy working memory load without articulatory confounds, controlling for the overall ability to match auditory words to pictures and to perform a metalinguistic rhyme judgement, isolating the effect of working memory load (103 individuals). We assessed non-canonical sentence comprehension, isolating syntactic processing by incorporating residual rhyme judgement performance as a covariate for working memory load (78 individuals). Voxel-based lesion analyses and structural connectome-based lesion symptom mapping controlling for total lesion volume were performed, with permutation testing to correct for multiple comparisons (4000 permutations). We observed that effects of working memory load localized to dorsal stream damage: posterior temporal-parietal lesions and frontal-parietal white matter disconnections. These effects were differentiated from syntactic comprehension deficits, which were primarily associated with ventral stream damage: lesions to temporal lobe and temporal-parietal white matter disconnections, particularly when incorporating the residual measure of working memory load as a covariate. Our results support the conclusion that working memory and syntactic processing are associated with distinct brain networks, largely loading onto dorsal and ventral streams, respectively.