Analysis Of Topographic Maps Research Articles

Evaluating Convolutional Neural Network Architecture for Historical Topographic Hardcopy Maps Analysis: A Study on Training and Validation Accuracy Variation

Convolutional Neural Networks (CNN) are widely used for image analysis tasks, including object detection, segmentation, and recognition. Given the advanced capability, this study evaluates the effectiveness and performance of CNN architecture for analysing Historical Topographic Hardcopy Maps (HTHM) by assessing variations in training and validation accuracy. The lack of research specifically dedicated to CNN’s application in analysing topographic hardcopy maps presents an opportunity to explore and address the unique challenges associated with this domain. While existing studies have predominantly focused on satellite imagery, this study aims to uncover valuable insights, patterns, and characteristics inherent to HTHM through customised CNN approaches. This study utilises a standard CNN architecture and tests the model’s performance with different epoch settings (20, 40, and 60) using varying dataset sizes (288, 636, 1144, and 1716 images). The results indicate that the optimal operation point for training and validation accuracy is achieved at epoch 40. Beyond epoch 40, the widening gap between training and validation accuracy suggests overfitting. Hence, adding more epochs does not significantly improve accuracy beyond the optimum phase. The experiment also shows that the CNN model obtains a training accuracy of 98%, validation accuracy of 67%, and F1-score overall performance of 77%. The analysis demonstrates that the CNN model performs reasonably well in classifying instances from the HTHM dataset. These findings contribute to a better understanding of the strengths and limitations of the model, providing valuable insights for future research and refinement of classification approaches in the context of topographic hardcopy map analysis.

Historical landscape structures of the eastern part of upper Medzibodrožie region

Landscape represents a specific part of the earth's surface, while it has its own structure – primary, secondary and tertiary. The secondary landscape structure consists of elements of land use and material creations of man, which currently fill the earth's surface. The aim of the paper is to evaluate, based on the analysis of historical military and topographical maps, the changes in the secondary landscape structure in the area formed by the cadastral territories of selected municipalities in the eastern part of Upper Medzibodrožie Region. On four maps showing selected territories of Upper Medzibodrožie Region, we compare extensive changes that have occurred in the landscape structure mainly as a result of human intervention in the landscape structure. Historical maps show that the use of the Upper Medzibodrožie Region landscape has changed significantly over the past 150 years. River regulation, drainage works, deforestation and also the transformation of agriculture had a major impact on these changes. The results show that the largest decrease in area representation was recorded by forests and the largest increase by arable land.

Theoretical Investigation on Dialumenes toward Dihydrogen Activation: Mechanism and Ligand Effect.

Herein, we report a computation study based on the density functional theory calculations to understand the mechanism and ligand effect of the base-stabilized dialumenes toward dihydrogen activation. Among all of the examined modes of dihydrogen activation using the base-stabilized dialumene, we found that the concerted 1,2-hydrogenation of the Al═Al double bond is kinetically more preferable. The concerted 1,2-hydrogenation of the Al═Al double bond adopts an electron-transfer model with certain asynchrony. That is, the initial electron donation from the H-H σ bonding orbital to the empty 3p orbital of the Al1 center is followed by the backdonation from the lone pair electron of the Al2 center to the H-H σ antibonding orbital. Combined with the energy decomposition analysis on the transition states of the concerted 1,2-hydrogenation of the Al═Al double bond and the topographic steric mapping analysis on the free dialumenes, we ascribe the higher reactivity of the aryl-substituted dialumene over the silyl-substituted analogue in dihydrogen activation to the stronger electron-withdrawing effect of the aryl group, which not only increases the flexibility of the Al═Al double bond but also enhances the Lewis acidity of the Al═Al core. Consequently, the aryl-substituted dialumene fragment suffers less geometric deformation, and the orbital interactions between the dialumene and dihydrogen moieties are more attractive during the 1,2-hydrogenation process. Moreover, our calculations also predict that the Al═Al double bond has a good tolerance with the stronger electron-withdrawing group (-CF3) and the weaker σ-donating N-heterocyclic carbene (NHC) analogue (e.g., triazol carbene and NHSi). The reactivity of the dialumene in dihydrogen activation can be further improved by introducing these groups as the supporting ligand and the stabilizing base on the Al═Al core, respectively.

MACHINE LEARNING AND ARTIFICIAL NEURAL NETWORK TECHNOLOGIES IN THE CLASSIFICATION OF POSTKERATOTOMIC CORNEAL DEFORMITY

Backgraund: A thorough analysis of both the optical and anatomical properties of the cornea in patients after anterior radial keratotomy is of particular importance in choosing the optical strength of an intraocular lens in the surgical treatment of cataracts and other types of optical correction. The variability of the clinical picture of postkeratotomic deformity (PCRD) determines the need to develop its classification and is an important task of modern ophthalmology.
 Aims: to develop an automated system of classification of corneal PCRD using machine learning and an artificial neural network based on the analysis of topographic maps of the cornea.
 Materials and methods: depersonalized results of the analysis of medical records of 250 patients aged 59.63±5.95 (from 46 to 76) years were used as the material. The analysis of 500 maps of the relief-topography of the anterior and posterior surfaces of the cornea and 3 stages of machine learning of the PCRD classification were carried out.
 Results: Stage 1- analysis of the relief topography of the anterior and posterior surfaces of the cornea allowed us to fix the numerical values of the elevation of the anterior and posterior surfaces of the cornea in three ring-shaped zones. At stage 2, in the course of deep machine learning, a direct distribution neural network was selected and created. 8 auxiliary parameters describing the shape of the anterior and posterior surfaces of the cornea were established. Stage 3 was accompanied by obtaining algorithms for the classification of PCRD depending on the ratio of test and training samples, which ranged from 75 to 91%..
 Conclusion: The use of artificial neural network algorithms can become a useful tool for automatic classification of postkeratotomic corneal deformity in patients who have previously undergone radial keratotomy.

Cross-subject emotion EEG signal recognition based on source microstate analysis

Electroencephalogram (EEG) signals are very weak and have low spatial resolution, which has led to less satisfactory accuracy in cross-subject EEG-based emotion classification studies. Microstate analyses of EEG sources can be performed to determine the important spatiotemporal characteristics of EEG signals. Such analyses can be used to cluster rapidly changing EEG signals into multiple brain prototype topographies, fully utilizing the spatial information contained in the EEG signals and providing a neural representation for emotional dynamics. To better utilize the spatial information of brain signals, source localization analysis on the EEG signals was first conducted. Then, a microstate analysis on the source-reconstructed EEG signals is conducted to extract the microstate features of the data. We conducted source microstate analysis on the participant data from the odor-video physiological signal database (OVPD-II) dataset. The experimental results show that the source microstate feature topologies of different participants under the same emotion exhibited a high degree of correlation, which was proven by the analysis of microstate feature topographic maps and the comparison of two-dimensional feature visualization maps of the differential entropy (DE) and power spectral density (PSD). The microstate features represent more abstract emotional information and are more robust. The extracted microstate features were then used with the style transfer mapping method to transfer the feature data from the source domain to the target domain and were then used in support vector machines (SVMs) and convolutional neural networks (CNNs) for emotion recognition. The experimental results show that the cross-subject classification accuracies of the microstate features in SVMs were 84.90 ± 8.24% and 87.43 ± 7.54%, which were 7.19 and 6.95% higher than those obtained with the PSD and 0.51 and 1.79% higher than those obtained with the DE features. In CNN, the average cross-subject classification accuracies of the microstate features were 86.44 and 91.49%, which were 7.71 and 19.41% higher than those obtained with the PSD and 2.7 and 11.76% higher than those obtained with the DE features.

Evaluation of the Topology Space of DNA-Encoded Libraries.

DNA-encoded libraries (DELs) are widely used in the discovery of drug candidates, and understanding their design principles is critical for accessing better libraries. Most DELs are combinatorial in nature and are synthesized by assembling sets of building blocks in specific topologies. In this study, different aspects of library topology were explored and their effect on DEL properties and chemical diversity was analyzed. We introduce a descriptor for DEL topological assignment (DELTA) and use it to examine the landscape of possible DEL topologies and their coverage in the literature. A generative topographic mapping analysis revealed that the impact of library topology on chemical space coverage is secondary to building block selection. Furthermore, it became apparent that the descriptor used to analyze chemical space dictates how structures cluster, with the effects of topology being apparent when using three-dimensional descriptors but not with common two-dimensional descriptors. This outcome points to potential challenges of attempts to predict DEL productivity based on chemical space analyses alone. While topology is rather inconsequential for defining the chemical space of encoded compounds, it greatly affects possible interactions with target proteins as illustrated in docking studies using NAD/NADP binding proteins as model receptors.

High-resolution core data and machine learning schemes applied to rock facies classification

Abstract This paper presents core analysis practices developed to increase the value of cores in reservoir characterization workflows. Core analysis traditionally implies extensive rock testing programmes that require large numbers of plug samples. Numerous stakeholders compete for intact core material and often do not base sample selection criteria on objective and reliable information. As a consequence, samples dedicated to core analysis programmes consume a significant fraction of the material available, yet they are selected on the basis of very little a priori information and therefore do not necessarily capture the complexity of the targeted formations. In an attempt to change this paradigm, we promote a more integrated core analysis solution combining transdisciplinary, high-resolution, non-destructive measurements on whole cores, for an early yet objective description of cores and the rapid estimation of formation properties. The first section describes multidisciplinary and non-destructive tests designed to increase the value of information from cores while keeping a minimal footprint. Core samples are scanned along a fit-for-purpose surface, with a collection of sensors interfaced to the same table-top equipment. Technologies including ultra-high-resolution pictures, elemental composition and the direct measurements of geomechanical properties provide continuous and high-resolution profiles with a unique depth reference. Panoramic pictures are processed to extract textural and colour features and grain size distributions. Grain size distributions are backed up by analysis of topographical maps created with a laser scan. The results are combined under one unique format, thereby easing interdisciplinary work from the verification of standard tests (routine core analysis, rock mechanical test) to the construction of robust predictive rock models. The paper describes machine learning schemes applied to core datasets. Unsupervised schemes are designed to identify rock facies, while supervised schemes are used to classify tested rocks into predefined rock facies with known petrophysical properties. Case studies highlight the benefits of this approach of core analysis in conjunction with artificial intelligence for the automated identification and classification of rock facies. This novel approach to core analysis leverages a detailed and comprehensive knowledge of the distributions of core properties, available under one unique format for all disciplines, which eases interdisciplinary work and significantly improves existing core analysis standards. It also provides a sound basis to train artificial intelligence rock reservoir property predictors linking well-log data to core-based lithofacies signatures.

Watershed characteristics of West Progo dome and its implications on neotectonic

This geomorphological study discusses the characteristics of the watershed that compose the West Progo Dome, conducted using a field survey method, topographic map analysis, and remote sensing imagery. This is because the West Progo Dome is built by two different litology characteristics (volcanic and carbonate rocks) and different age. Analysis of watershed characteristics includes area, flow pattern, bifurcation ratio (Rb), and river density (Dd), accompanied by statistical analysis of the T2-Hotelling multivariate mean difference test. The results shows that the West Progo Dome has three large watersheds, namely the Bogowonto, Serang, and Progo watersheds, with an area of about 270.4, 110.9, and 140.3 km2, respectively. The drainage patterns in this area are dendritic, radial, sub-parallel, trellis, rectangular and angulate. Rb of drainage in the study area varies from low to high, indicating the presence of tectonic influences. The Rb value in System IIA is 2.0 - 5.8, and in System III is 1.290 - 6.630. The Dd value on System IIA is 0.921-1.592 km/km2 and on System III is 0.990-1.200 km/km2. This very rough Dd also indicates the presence of tectonic influences. The average Rb and Dd values between System IIA and System III were not significantly different. It means that tectonics influences the watershed morphometry in the West Progo Dome and is still active until the Quaternary (neotectonic).

Changes in the stream discharge in the forest-steppe zone in the XXI century under the environmental regime (based on the research of the dynamics of the length of the channel network of elementary watercourses on the territory of the “Sengileevskie Mountains” National Park Ulyanovsk region, Russia))

The article presents the results of researching changes in the stream discharge in the forest-steppe zone in the XXI century in the conditions of the environmental regime. Due to the lack of data on the stream discharge within the researched area in previous years, the length of the channel network is considered as an indicator of water content – an indicator that generally correlates with the value of the length of the channel network. Elementary watercourses are taken as the object of research, since in short periods they are able to show high variability under the influence of external conditions, especially if it is necessary to establish the influence of specific local factors. The research was conducted on the territory of the “Sengileevskie Mountains” National Park, which lies within the Volga landscape region and the Low Volga region in the forest-steppe zone. This territory exists in the conditions of the nature protection regime and has a high forest cover. The research was based on the materials of the expedition work carried out in the summer of 2022. and the results of geoinformation analysis of topographic maps reflecting the position of the sources of elementary watercourses in 2001. As a result of the expedition work, the length of the channels of elementary watercourses as of 2022 has been established, the indicator of the change in the length of their channels in the XXI century – from 2001 to 2022 has been calculated. The fact of the multidirectional dynamics of the length of the channel network of elementary watercourses is established. In the conditions of the nature protection regime established at the beginning of the XXI century, against the background of the restoration of the landscapes of the researched territory, there is an increase in the length of the channel network of elementary watercourses, which has a correlation with the areal indicators of the restoration of natural plant communities – forests and meadows.

Semi-supervised learning for topographic map analysis over time: a study of bridge segmentation

Geographical research using historical maps has progressed considerably as the digitalization of topological maps across years provides valuable data and the advancement of AI machine learning models provides powerful analytic tools. Nevertheless, analysis of historical maps based on supervised learning can be limited by the laborious manual map annotations. In this work, we propose a semi-supervised learning method that can transfer the annotation of maps across years and allow map comparison and anthropogenic studies across time. Our novel two-stage framework first performs style transfer of topographic map across years and versions, and then supervised learning can be applied on the synthesized maps with annotations. We investigate the proposed semi-supervised training with the style-transferred maps and annotations on four widely-used deep neural networks (DNN), namely U-Net, fully-convolutional network (FCN), DeepLabV3, and MobileNetV3. The best performing network of U-Net achieves F1_{inst:0.1} = 0.725 and F1_{inst:0.01} = 0.743 trained on style-transfer synthesized maps, which indicates that the proposed framework is capable of detecting target features (bridges) on historical maps without annotations. In a comprehensive comparison, the F1_{inst:0.1} of U-Net trained on Contrastive Unpaired Translation (CUT) generated dataset (0.662 pm 0.008) achieves 57.3 % than the comparative score (0.089 pm 0.065) of the least valid configuration (MobileNetV3 trained on CycleGAN synthesized dataset). We also discuss the remaining challenges and future research directions.

Perceived gaze direction affects recollection processes in recognition of concrete and abstract words: electrophysiological evidence.

Studies have revealed that memory performance can be affected by perceived gaze direction. However, it remains unclear whether direct gaze promotes or hinders word memory, and the effect of gaze direction on memory of words with different concreteness requires investigation. In the study phase, concrete and abstract words were presented on direct- or averted-gaze faces, and participants were instructed to judge gaze direction and memorize words. In the test phase, participants were asked to discriminate whether a word was old or new. Electroencephalogram recordings were taken in both phases. Behavioral and time-frequency results verified the direct-gaze memory advantage, showing that memory performance was better in the direct-gaze condition than the averted-gaze condition for both concrete and abstract words. Event-related potential results showed that in both direct- and averted-gaze conditions, the early old/new effects (FN400) associated with familiarity were only elicited for concrete words but not abstract words. The late old/new effects (LPC) associated with recollection were elicited in all conditions. More importantly, concrete words elicited greater LPC than abstract words in the direct-gaze condition, whereas there was no such significant LPC difference in the averted-gaze condition. Topographic map analysis found that neural generators between concrete and abstract words differed in the direct-gaze condition but not in the averted-gaze condition. The study supports the hypothesis that direct-gaze promotes memory performance. Furthermore, it is mainly in memory recollection that gaze direction affects words with different concreteness.

Promising Technology Analysis and Patent Roadmap Development in the Hydrogen Supply Chain

Hydrogen energy, one of the energy sources of the future, represents a substantial issue which affects the industries and national technologies that will develop in the future. In order to utilize hydrogen energy, a hydrogen supply chain is required so that hydrogen can be processed and transported to vehicles. It is helpful for technology and policy development to analyze technologies necessary to charge the hydrogen energy generated into vehicles through the supply chain to discover technologies with high potential for future development. The purpose of this paper is to identify promising technologies required in storing, transporting, and charging vehicles generated by the hydrogen fuel supply chain. Afterward, the promising technologies identified are expected to help researchers set a direction in researching technologies and developing related policies. Therefore, we provide technology information that can be used promisingly in the future so that researchers in the related field can utilize it effectively. In this paper, data analysis is performed using related patents and research papers for technical analysis. Promising technologies that will be the core of the hydrogen fuel supply chain in the future were identified using the published patents and research paper database (DB) in Korea, the United States, Europe, China, and Japan. A text mining technique was applied to preprocess data, and then a generic topographic map (GTM) analysis discovered promising technologies. Then, a technology roadmap was identified by analyzing the promising technology derived from patents and research papers in parallel. In this study, through the analysis of patents and research papers related to the hydrogen supply chain, the development status of hydrogen storage/transport/charging technology was analyzed, and promising technologies with high potential for future development were found. The technology roadmap derived from the analysis can help researchers in the field of hydrogen research establish policies and research technologies.

Landform Geomorphology Classification of Ashkaft Fold

Land classification means unifying the shapes of the earth's surface and categorizing them into groups arranged according to a hierarchical hierarchical system that extends from the major terrestrial systems to the smaller terrestrial units Land forms are the result of a number of factors, the most important of which are (structural, climatic, hydrological and biological factors), as their effects are intertwined between the forces of resistance and the forces of movement in the formation of the land appearance, and by the energy they carry, they change the surface of the earth through its external processes (weathering and erosion forces) represented by physical variables. And the chemicals that play the main role in the evolution of the terrain, for example, weathering works to prepare the rocky crumbs for movement of different types: air and water, and the elements of climate have an effective role in activating geomorphic processes, as well as living organisms, humans, animals, and microorganisms. For this reason, the study of the landforms that resulted from the geomorphological factors and processes within the study area, through the analysis of topographic maps, and aerial photographs covering the study area according to what is available, in addition to documenting these forms in the field through the field study. The researcher relied on the global (ITC) system issued by the Space Research Center in the Netherlands, to classify the landforms, and according to what is in circulation, it is one of the best systems adopted in the departments (geographical and geological), which is based in its classification of landforms on the nature of geomorphological factors and processes Responsible for the formation of these forms, this is what is done and preferred by most geomorphologists in the world

Morphotectonics, Seismicity, and Exogenous Processes of the Kola Peninsula

Abstract—The purpose of this study is to determine a morphologically pronounced fault–block structure identified with the neotectonic stage and compare it with sites with manifested exogenous processes, as well as modern and historical paleoseismicity in order to establish faults activated in the postglacial time. Based on the analysis of space images (Landsat-ETM+) and a digital elevation model (GTOPO-30), the territory of the Kola Peninsula and the adjacent part of North Karelia is subjected to morphostructural interpretation with identifying morpholineaments and an elementary block structure. It is shown by the analyzing the directions and extent of elementary, single (simple), and complex (echeloned, parallel conjugated, and imbricated) linear structures and their zones that both linear (fault) and areal (block) structures are characterized by a predominance of a single system of northwestern and northeastern differences with a clear dominance of the former and unimodal distribution of the extent of faults and the area of blocks, depending on their number. This indicates a single (recent) stage in the formation of the morphotectonic appearance of the territory and no discrete hierarchy of the morphostructures. The degree of fragmentation of the territory at different depths is calculated depending on the number and extent of morpholineaments. It is determined that morpholineaments have a high degree of inheritance from Archean–Proterozoic structures (≈50%). Elementary morphotectonic blocks are grouped into composite blocks bounded by linear zones of great extent (100–600 km) having individual physiognomic features determined by fault patterns, which indicates the nature of the neotectonic dynamics and the degree of inheritance or reformation of the structural plan. The localization of manifestations of exogenous processes, epicenters of paleo-, historical, and modern earthquakes is determined on the basis of the analysis of topographic maps scaled at 1:100,000, catalogs of historical and paleoearthquakes, and the consolidated literature (including the data obtained by the authors of this study) on paleoseismic deformations. A geoinformation base is compiled, which is used to simulate the spatial distribution of endo- and exogenous signs of tectonic activity and compare it with the neotectonic fault–block structure. The spatial similarity of endogenous and exogenous activation zones and their confinement to faults, defined as activated in the postglacial time, are revealed. It is revealed that the following elements are most active in the postglacial–Holocene. First, flank elements on the Kola Peninsula along the Barents Sea coast, the Kandalaksha Bay shores, and the Gorlo Strait of the White Sea. Second, the central (nodal) part with the Khibiny and Lovozero massifs. Third, submeridional (transverse) secant structures separating the eastern part of the peninsula from the western part (Khibiny–Kola and Khibiny–Niva). The spatial parameters of the activated zones indicate a range of earthquake magnitudes M ≈ 6.5–7.5 generated by these structures both in the postglacial period and in the Neopleistocene as a whole.

Morphometry Analysis of Sedayu Mountainous Catchment Areas from Detailed Aerial Photos

Morphometric analysis is a powerful tool to understand the hydrological process quantitatively and the main requirement to determine the hydrological characteristics of a watershed. Morphometric analysis to determine the drainage characteristics of the Sedayu River Sub-watershed, Semaka District, Tanggamus Regency, Lampung Province was carried out using Digital Elevation Model (DEM) data. The primary data used is aerial photography using drones, the location of aerial photos representing watersheds of concern. The catchment area morphometrics were obtained from the extraction of the morphometric characteristics of the combined DEM data from the mountain watershed and the analysis of topographic maps by using ArcGIS software. Based on reports over a period of time, at several points in the area there are frequent river floods that overflow during heavy rains. Morphometric analysis in flood-prone areas with high rainfall is needed. The morphology of the Sedayu area has contrasting variations consisting of several gentle alluvial plains, some of which are Bukit Barisan hills with varying slope variations. The Sedayu watershed in this study is divided into 3 sub-watersheds, namely: sub-watershed A, sub-watershed B, and sub-watershed C. However, only sub-watershed A is the focus of morphometric analysis because its longest river, record flood disasters, landslide records, and has upstream to residential. Morphometric analysis was carried out on parameters such as watershed area (A), watershed length (Lb), main river length (Ln ), watershed width (W), drainage density (Dd ), bifurcation ratio (Rb ), and circularity ratio (Rc ). The results of morphometric calculations are the length of the watershed 4.82 km, the length of the main river is Sub-watershed A 8.996 km, the width of the watershed 0.686 km, and watershed area 4.861 km2 Based on these results can be calculated drainage density (Dd ) 2.719 km/km2 which means Sub-watershed A of a rough type with the inundated surface, permeable sub-soil, and resistant to erosion. Bifurcation ratio (Rb ) is 3.333 which means sub-watershed A has a rapid rise and fall in floodwater. Then, the circularity Ratio (Rc ) 0.32 which means Sub-watershed A is elongated so that the peak discharge and decrease flow quickly and causes a link with the hydrological response of rainfall-runoff. The results of this morphometric characteristic analysis are the right reference for planning strategies for soil erosion control and soil conservation.

Geological aspect analysis for micro hydro power plant site selection based on remote sensing data

<span>Geological characters analysis is essential for micro hydropower plant (MHP) development planning. This paper presents an analysis of the geological aspect to determine the layout of MHP components based on remote sensing data as part of a solution to addressing power shortages in Sungai Are District, South Ogan Komering Ulu Regency, South Sumatra Province. Remote sensing and topographic map were extracted to identify the potential site. The topographic map and geological analysis were used to calculate the potential of electrical energy and the geological hazard risk, particularly floods and landslides. The results of the study identified four potential sites. Site 1 (Luas River, Ulu Danau Village) and site 3 (Putih River, Gintung Village) are suitable for MHP with a low cost of construction. Site 2 (Pecah Pinggan Village) and site 4 (Simpang Luas Village) are prone to flooding and landslides that makes it suitable for MHP but with a high cost of construction. Based on the geological aspect analysis, it is possible to optimize the hydropower capacity, by adding the volume of water flow from several nearby tributaries channeled into the hydropower flow system through civil construction engineering or by making a cascade design on the tailrace water flow.</span>

Large-scale topography of the north Tibetan ranges as a proxy for contrasted crustal-scale deformation modes

Forming the northern margin of the Cenozoic Himalayan–Tibetan orogen, the area surrounding the Qaidam Basin is a key region to study the mechanisms that govern the long-term evolution of intracontinental orogenic processes. Indeed, tectonic deformation in this region involves newly formed and inherited crustal and lithospheric structures, partition between horizontal and vertical movements, and a strong influence from external factors such as climate and erosion. This study proposes a description of the topography and crustal structure of the north Tibet ranges as an insight into their tectonic deformation characteristics. The topographic study includes the integrated analysis of regional topographic profiles, river profiles, slope maps and thermochronology data. The available geophysical, geological and structural data are used to draw regional, crustal-scale geological sections across northern Tibet to describe the regional crustal structure. We show that three deformation modes are expressed (block uplift, distributed shortening and crustal buckling) in structural compartments that involve either complete mountain ranges or some specific regions inside those ranges. We propose that a new crustal structure may develop parallel to the Altyn Tagh fault, connecting the eastern tip of the Qimen Tagh with the Haiyuan fault, across the Qaidam Basin. Supplementary material : Supplementary figures are available at https://doi.org/10.6084/m9.figshare.c.5841461 Thematic collection: This article is part of the Fold-and-thrust belts collection available at: https://www.lyellcollection.org/cc/fold-and-thrust-belts

Mechanisms of False Alarm in Response to Fear Stimulus: An Event-Related Potential Study.

Background and ObjectiveThere is a paucity of research that has explored “False Alarm” mechanisms. In order to remedy this deficiency in knowledge, the present study used event-related potential (ERP) technology to reveal the mechanisms underlying False Alarm in response to fear stimuli.MethodsThis study selected snakes as experimental materials and the “oddball paradigm” was used to simulate the conditions of False Alarm. The mechanism underlying False Alarm was revealed by comparing cognitive processing similarities and differences between real snakes and toy snakes.ResultsEvent-related potential findings demonstrated that there was no significant difference between N1 and P2 components induced by real and toy snakes in the early processing stage. Compared with toy snakes, real snakes induced smaller N2 amplitude, larger P3 amplitude, and a shorter P3 latency at the late processing stage. The results of brain topographic mapping analysis showed that the brain regions activated by a real or toy snake were basically the same within the time windows of 110–150 and 220–270 ms, respectively. In the time window of 300–360 and 400–500 ms, the degree of brain regions activation with a real snake was significantly greater than that induced by a toy snake.ConclusionFalse Alarm is caused by the brain’s inability to distinguish, in the early stage of cognitive processing, stimulus objects with similar appearances. When the brain is able to distinguish the differences between different stimulus objects in the late stage of cognitive processing, False Alarm disappears.

Exploring Future Promising Technologies in Hydrogen Fuel Cell Transportation

The purpose of this research was to derive promising technologies for the transport of hydrogen fuel cells, thereby supporting the development of research and development policy and presenting directions for investment. We also provide researchers with information about technology that will lead the technology field in the future. Hydrogen energy, as the core of carbon neutral and green energy, is a major issue in changing the future industrial structure and national competitive advantage. In this study, we derived promising technology at the core of future hydrogen fuel cell transportation using the published US patent and paper databases (DB). We first performed text mining and data preprocessing and then discovered promising technologies through generative topographic mapping analysis. We analyzed both the patent DB and treatise DB in parallel and compared the results. As a result, two promising technologies were derived from the patent DB analysis, and five were derived from the paper DB analysis.

НОВЫЕ ПОДХОДЫ К ОТОБРАЖЕНИЮ МЕРЗЛОТНЫХ ФОРМ РЕЛЬЕФА НА ЦИФРОВЫХ ТОПОГРАФИЧЕСКИХ КАРТАХ СИБИРСКОЙ ЗОНЫ АРКТИКИ

The analysis of traditional topographic maps and plans of the Siberian Arctic zone shows that their relevance and completeness of content do not fully meet the modern requirements for the further de-velopment of this region. There is a need for targeted specialization of a new generation of topograph-ic maps and plans of Arctic territories, taking into account their physical and geographical specifics. The purpose of the work was to determine the possibility of such specialization based on the use of remote sensing materials from space and computer technologies.To achieve this goal, studies have been conducted to determine the visual and automated decryption capabilities of Landsat Sentinel sat-ellite images in order to expand and refine the existing system of conventional signs of cryogenic re-lief. Based on these studies, new conventional signs for polygonal, bumpy, solifluctional and thermo-karst forms are proposed. The conclusion is made about the need for specialization of other specific elements of Arctic maps – vegetation, hydrography, soils.