Complex Mapping Research Articles

Cadastral and landscape modeling of lakes as a prerequisite for protected and recreational nature resource management

The cadastral information about the lakes of the nature reserve fund (NRF) should be based on landscape-geographic principles using modern geo-information systems.Within the research, based on the instrumental field research and the use of software packages ArcGIS Desktop and ReefMaster Software, a bathymetric map of Lake Serednie (Nobel National Natural Park, Ukraine) and other spatial models were developed. The main hydrological and morphometric parameters of the lake basin were calculated, a landscape map of the natural aquatic complex was created and its landscape metric analysis was carried out at the level of aquatic tracts and facies. The research revealed changes in the level regime and shoreline of the lake caused by the long dry periods of 2016-2021 and life activity of beavers. The created integrated cadastral landscape model of the lake with limnology parameters should serve as a basis for the recreational nature use, monitoring and geo-ecological certification of the reservoirs of the NRF.

Identification of ferroptosis-related genes in type 2 diabetes mellitus based on machine learning.

Type 2 diabetes mellitus (T2DM), which has a high incidence and several harmful consequences, poses a severe danger to human health. Research on the function of ferroptosis in T2DM is increasing. This study uses bioinformatics techniques identify new diagnostic T2DM biomarkers associated with ferroptosis. To identify ferroptosis-related genes (FRGs) that are differentially expressed between T2DM patients and healthy individuals, we first obtained T2DM sequencing data and FRGs from the Gene Expression Omnibus (GEO) database and FerrDb database. Then, drug-gene interaction networks and competitive endogenous RNA (ceRNA) networks linked to the marker genes were built after marker genes were filtered by two machine learning algorithms (LASSO and SVM-RFE algorithms). Finally, to confirm the expression of marker genes, the GSE76895 dataset was utilized. The protein and RNA expression of some marker genes in T2DM and nondiabetic tissues was also examined by Western blotting, immunohistochemistry (IHC), immunofluorescence (IF) and quantitative real-time PCR (qRT-PCR). We obtained 58 differentially expressed genes (DEGs) associated with ferroptosis. GO and KEGG enrichment analyses showed that these DEGs were significantly enriched in hypoxia and ferroptosis. Subsequently, eight marker genes (SCD, CD44, HIF1A, BCAT2, MTF1, HILPDA, NR1D2, and MYCN) were screened by LASSO and SVM-RFE machine learning algorithms, and a model was constructed based on these eight genes. This model also has high diagnostic power. In addition, based on these eight genes, we obtained 48 drugs and constructed a complex ceRNA network map. Finally, Western blotting, IHC, IF, and qRT-PCR results of clinical samples further confirmed the results of public databases. The diagnosis and aetiology of T2DM can be greatly aided by eight FRGs, providing novel therapeutic avenues.

Inversion analysis of rock mass permeability coefficient of dam engineering based on particle swarm optimization and support vector machine: A case study

In order to efficiently and reasonably determine the permeability coefficient of engineering rock mass, the two key problems of complex seepage field simulation and objective function solution in permeability coefficient inversion are studied and improved. Firstly, a 3D refined seepage numerical model is established considering the main fault fracture zones and dam seepage control system. Secondly, combined with the support vector machine (SVM) algorithm, the complex mapping relationship between permeability coefficient of each rock layer and impervious structure and piezometer head is constructed. Finally, the particle swarm optimization (PSO) algorithm is introduced, and then the efficient optimization of permeability coefficient inversion of engineering rock mass and impervious structure is realized based on PSO-SVM. The case study of LJH arch dam shows that the inversion calculation framework based on PSO-SVM not only completes the rapid proxy calculation of the numerical model of complex seepage field, but also realizes the accurate optimization of the inversion objective function. The simulation results under the final inversion parameters reproduce the variation characteristics of the piezometric tube water level of each typical measuring point under the change of reservoir water level. In addition, with the correlation analysis between the permeability coefficient and the measured value of the corresponding piezometer, the parameter inversion method is endowed with new application value. This study is of great significance for clarifying the seepage characteristics of complex rock mass and improving the inversion efficiency of dam seepage monitoring data.

An examination of force maps targeted at orientation interactions in moving groups.

Force mapping is an established method for inferring the underlying interaction rules thought to govern collective motion from trajectory data. Here we examine the ability of force maps to reconstruct interactions that govern individual's tendency to orient, or align, their heading within a moving group, one of the primary factors thought to drive collective motion, using data from three established general collective motion models. Specifically, our force maps extract how individuals adjust their direction of motion on average as a function of the distance to neighbours and relative alignment in heading with these neighbours, or in more detail as a function of the relative coordinates and relative headings of neighbours. We also examine the association between plots of local alignment and underlying alignment rules. We find that the simpler force maps that examined changes in heading as a function of neighbour distances and differences in heading can qualitatively reconstruct the form of orientation interactions, but also overestimate the spatial range over which these interactions apply. More complex force maps that examine heading changes as a function of the relative coordinates of neighbours (in two spatial dimensions), can also reveal underlying orientation interactions in some cases, but are relatively harder to interpret. Responses to neighbours in both the simpler and more complex force maps are affected by group-level patterns of motion. We also find a correlation between the sizes of regions of high alignment in local alignment plots and the size of the region over which alignment rules apply when only an alignment interaction rule is in action. However, when data derived from more complex models is analysed, the shapes of regions of high alignment are clearly influenced by emergent patterns of motion, and these regions of high alignment can appear even when there is no explicit direct mechanism that governs alignment.

MR Elastography With Optimization-Based Phase Unwrapping and Traveling Wave Expansion-Based Neural Network (TWENN).

Magnetic Resonance Elastography (MRE) can characterize biomechanical properties of soft tissue for disease diagnosis and treatment planning. However, complicated wavefields acquired from MRE coupled with noise pose challenges for accurate displacement extraction and modulus estimation. Using optimization-based displacement extraction and Traveling Wave Expansion-based Neural Network (TWENN) modulus estimation, we propose a new pipeline for processing MRE images. An objective function with Dual Data Consistency (Dual-DC) has been used to ensure accurate phase unwrapping and displacement extraction. For the estimation of complex wavenumbers, a complex-valued neural network with displacement covariance as an input has been developed. A model of traveling wave expansion is used to generate training datasets for the network with varying levels of noise. The complex shear modulus map is obtained through fusion of multifrequency and multidirectional data. Validation using brain and liver simulation images demonstrates the practical value of the proposed pipeline, which can estimate the biomechanical properties with minimal root-mean-square errors when compared to state-of-the-art methods. Applications of the proposed method for processing MRE images of phantom, brain, and liver reveal clear anatomical features, robustness to noise, and good generalizability of the pipeline.

Process Modeling for Crisis Management

Crisis management is one form of management. It is applied in situations that we refer to as crisis. A crisis is a stressful situation for all interested parties, in which there is a greater or lesser threat to the values and assets. Coping with a crisis situation depends on many factors, while preparation is absolutely necessary, which must be done at a time when there is no crisis and ideally there is no threat. This preparation must also include the definition of crisis processes, i.e. the description of the behavior of each subject. At the time of crisis activation, everyone must know what rights and obligations they have and how they should fulfill these tasks. For the definition and description of these processes, it is possible to use proven means of process modeling, which have been used for a long time in many fields of human activity. An appropriately described process model, or a complex process map, can then be the optimal source of information for all entities.

Structuring Complex or Wicked Problems: A Multimethod Approach in Practice

Complex or wicked problems necessarily require multidisciplinary approaches to shape the issue(s) into a structure that can lead to viable solutions. This paper presents a case in which a systematic approach was used to combine structuring methods to support a research design that intended to quantitatively relate variables which have been insufficiently defined. Misconstrued definitions of variables and the dearth or missing data are just some of the characteristics that make this problem “complex.” The scientist’s primary work in the early stages of this type of research effort is to apply a series of techniques that meaningfully define the variables, specify relevant data to support development of quantitative models, and generate and\or collect that data. The sequence of discussion in this paper is a multimethod outline for addressing complex problems. This paper begins by defining complex or wicked problems. Next, an illustrative military problem that exhibits complex characteristics is presented. Sequentially, various structuring techniques from several fields of study such as systems engineering, operations research, and computer science are discussed and applied to the problem. Activities began with a workshop to learn about the problem and provide context. This venue allowed primary stakeholders to describe the variables from their stance. During the workshop, participants conceptualized relationships among the variables. An in-depth literature review before and after the workshop informed development of theories and hypotheses about the variables and plausible connections among them. Using functional decomposition, the team broke down the variables into their fundamental components. Relational matrices and causal loop diagrams formed initial ideas for how the components may be linked. Functional decomposition syntax also led to relevant, quantifiable measures that afforded an opportunity to mathematically formulate relationships among components, thereby achieving the primary objective of the problem. Blending techniques from different disciplines and their respective structuring methods is a powerful approach for creating conditions to solve complex or wicked problems. The utility of this study is in identifying the critical properties of a complex or wicked problem and mapping suitable methods to “tame” them. The overall approach is applicable to complex problems found in industry, government, and scientific research.

Regional application of complex groundwater quality indices and mapping for the territory of Bulgaria with possibilities for their use

The aim of this study is to perform a spatial complex hydrochemical analysis of groundwater quality in Bulgaria and compile a map. For this purpose, data for the chemical composition (Ca2+, Mg2+, Na+, Cl–, SO42–, NO3–, HCO3–, TDS, EC) of fresh groundwater (having shallow circulation) for the year 2015 have been summarized. These are the waters most vulnerable to incoming contaminants infiltrating from the surface and, at the same time, these are the waters of importance for the provision of potable water supply. The Groundwater Quality Index has been used to assess the water quality for domestic usage. An assessment of the potential groundwater’s corrosive activity has also been made. For this purpose, the Langelier Saturation Index and the Potential to Promote Galvanic Corrosion were determined as well. The galvanic corrosion of water in respect to lead (expressed as the chloride-sulphate mass ratio) has not been determined and mapped on the territory of Bulgaria, nor has the Langelier index for fresh groundwater. For the year of 2015, the groundwater of the territory was classified as being in acceptable (76 to 90), and good (90 to 95) condition in terms of the Groundwater Quality Index. In terms of the Langelier Saturation Index and the Potential for Galvanic Corrosion, the territory of the country can be characterized by low to moderate potential (for galvanic corrosion), and according to LSI it can be classified in three categories – potentially corrosive, indeterminate, and scale forming.

Assessing the Degradation of Safety Management Performance in Large Construction Projects: An Investigation and Decision Model Based on Complex Network Modeling

Modern safety control theory suggests that the accumulation of safety management defects at the organizational level can lead to a degradation in the overall safety management performance. This problem is exacerbated by the increasing complexity of safety management in large construction projects. The theoretical frameworks proposed by existing studies can provide generalized guidance for identifying safety management defects, but they are not flexible enough to address the complexity of a safety management system (SMS) in specific large construction projects. This study proposed an investigation and decision model based on a complex network model of SMSs. The main purpose was to accurately assess the degradation of safety management performance through the comprehensive identification of safety management defects for large construction projects. The functional components and their interactions in SMSs were graphically represented in a complex network using the fuzzy DEMATEL technique. Based on this, deep-seated safety management defects were identified by tracing the path of influence between the functional components and their roots. Furthermore, the results of this identification were used to support the assessment of the degradation of the safety performance of the overall SMS. The proposed model was verified with a large-scale wastewater treatment plant construction project in Lanzhou City, China. The degradation of the functional components could be presented in a complex visual network map to facilitate an understanding of the weak points or risk-sensitive areas throughout the SMS. Especially in the case of false safety perceptions, deep-seated safety management defects can be identified in time to prevent a sudden collapse of the SMS through early warnings. In addition, it also facilitates timely short-term improvement strategies and systematic long-term improvement strategies for long-term sustainability and increased resilience.

ВЫДЕЛЕНИЕ АМПЕЛОЭКОТОПОВ ДЛЯ ЭФФЕКТИВНОГО ВЫРАЩИВАНИЯ ВИНОГРАДА В СЕВАСТОПОЛЬСКОМ РЕГИОНЕ

The article presents the research results on the degree of favorability of agro-ecological conditions of Sevastopol for grapevine cultivation. The analysis according to the available multi-year data of weather stations of the Crimean peninsula is given. The following climatic indices characterizing vegetation period and grape ripening period were calculated: sum of temperatures above 20°C, ratio of sum of temperatures above 20 °C to sum of temperatures above 10 °C, Huglin and Winkler indices, average temperature of vegetation period, Selyaninov hydrothermal coefficient, sum of precipitation per year and vegetation period. Besides, the main agro-ecological factors limiting the possibility and efficiency of grapevine cultivation were considered: average of absolute minima of air temperature and sum of active temperatures above 10 °С. A digital complex map of the spatial distribution of these indices on the analyzed territory was constructed by means of geoinformation modeling. The distribution of Sevastopol territories that are not suitable for vineyards establishment was analyzed: with unfavorable soil conditions, with a height of more than 600 m above sea level, with a slope of over 20 degrees, as well as lands of forest and reserve funds. As a result of a comprehensive analysis of agro-ecological conditions in the territory of Sevastopol 9 ampeloecotopes were identified. According to the results of the comparison of agro-ecological conditions of the selected ampeloecotopes with the requirements of grapevine varieties to growing conditions, taking into account the dependence of the quality indicators of viticulture and winemaking products on agro-ecological factors, recommendations for agroecological optimization of the varietal composition and terroir specialization of the viticulture and winemaking industry in the territory of the city of federal significance − Sevastopol were developed.

The visual complexity of bike maps

Abstract. More and more cities try to encourage residents to cycle more. Therefore, governments are developing comprehensive bike maps to facilitate trip planning and increase the popularity of cycling. However, research on the topic of bike maps is rare and the versatility of possible features shown on a bike map makes these visually more complex than others. To understand how base maps and the display of cycling related features affect the visual complexity of bike maps and thus their effectiveness, we used different metrics (GMLMT, Subband Entropy, Edge Density, Feature Congestion, and Distinct Object-Type Counts) on four bike maps with four different visual complexity levels. We ran an eye-tracking experiment with 35 participants solving four different everyday tasks with these four bike maps. The findings suggest that adding more detail to base maps and displaying more cycling related features on a map resulted in a visually more complex bike map. Size, shape, and colour were found to have the biggest influence on the applied metrics. The analysis of eye-tracking data revealed that the display of cycling related features can affect the time needed for successfully completing a task. To deepen the gained understanding, further research should in more detail investigate how base maps influence bike maps efficiency.

Complex Mapping between Neural Response Frequency and Linguistic Units in Natural Speech.

When listening to connected speech, human brain can extract multiple levels of linguistic units, such as syllables, words, and sentences. It has been hypothesized that the time scale of cortical activity encoding each linguistic unit is commensurate with the time scale of that linguistic unit in speech. Evidence for the hypothesis originally comes from studies using the frequency-tagging paradigm that presents each linguistic unit at a constant rate, and more recently extends to studies on natural speech. For natural speech, it is sometimes assumed that neural encoding of different levels of linguistic units is captured by the neural response tracking speech envelope in different frequency bands (e.g., around 1 Hz for phrases, around 2 Hz for words, and around 4 Hz for syllables). Here, we analyze the coherence between speech envelope and idealized responses, each of which tracks a single level of linguistic unit. Four units, that is, phones, syllables, words, and sentences, are separately considered. It is shown that the idealized phone-, syllable-, and word-tracking responses all correlate with the speech envelope both around 3-6 Hz and below ∼1 Hz. Further analyses reveal that the 1-Hz correlation mainly originates from the pauses in connected speech. The results here suggest that a simple frequency-domain decomposition of envelope-tracking activity cannot separate the neural responses to different linguistic units in natural speech.

A Comprehensive Approach to Polarization Evolution

We extend earlier work on polarization conventions and provide a comprehensive analysis of the effect of both complex sign convention (CSC) and mapping conventions on the representation of Jones and Stokes polarization transformations. Both CSC forms are applied in parallel throughout the text to show their similar and dissimilar properties. Conditions for consistent translation of basis transformations for both CSCs and both representations are developed, and we show the details of an Euler angle approach that aids in those translations. Connecting to Stokes' original paper, we also reformulate the fundamentals of Stokes vectors, developing consistency constraints on their representations and illustrating violation of these by at least one well-known reference.

Path Planning for Mount Robot Based on Improved Particle Swarm Optimization Algorithm

To address the problem of cooperative work among right-angle coordinate robots in spacecraft structural plate mount tasks, an improved particle swarm optimization (PSO) algorithm was proposed to assign paths to three robots in a surface-mounted technology (SMT) machine. First, the optimization objective of path planning was established by analyzing the working process of the SMT machine. Then, the inertia weight update strategy was designed to overcome the early convergence of the traditional PSO algorithm, and the learning factor of each particle was calculated using fuzzy control to improve the global search capability. To deal with the concentration phenomenon of particles in the iterative process, the genetic algorithm (GA) was introduced when the particles were similar. The particles were divided into elite, high-quality, or low-quality particles according to their performance. New particles were generated through selection and crossover operations to maintain the particle diversity. The performance of the proposed algorithm was verified with the simulation results, which could shorten the planning path and quicken the convergence compared to the traditional PSO or GA. For large and complex maps, the proposed algorithm shortens the path by 7.49% and 11.49% compared to traditional PSO algorithms, and by 3.98% and 4.02% compared to GA.

Bodyformer: Semantics-guided 3D Body Gesture Synthesis with Transformer

Automatic gesture synthesis from speech is a topic that has attracted researchers for applications in remote communication, video games and Metaverse. Learning the mapping between speech and 3D full-body gestures is difficult due to the stochastic nature of the problem and the lack of a rich cross-modal dataset that is needed for training. In this paper, we propose a novel transformer-based framework for automatic 3D body gesture synthesis from speech. To learn the stochastic nature of the body gesture during speech, we propose a variational transformer to effectively model a probabilistic distribution over gestures, which can produce diverse gestures during inference. Furthermore, we introduce a mode positional embedding layer to capture the different motion speeds in different speaking modes. To cope with the scarcity of data, we design an intra-modal pre-training scheme that can learn the complex mapping between the speech and the 3D gesture from a limited amount of data. Our system is trained with either the Trinity speech-gesture dataset or the Talking With Hands 16.2M dataset. The results show that our system can produce more realistic, appropriate, and diverse body gestures compared to existing state-of-the-art approaches.

ВЫДЕЛЕНИЕ ПЕРСПЕКТИВНЫХ ТЕРРИТОРИЙ ДЛЯ ВЫРАЩИВАНИЯ ВИНОГРАДА В ВОСТОЧНОЙ ЧАСТИ СТЕПНОЙ ЗОНЫ КРЫМА

The article presents the results of studies of the degree of favorability of agroecological conditions of the eastern part of the Steppe zone of Crimea for growing grapevine. The long-term data on weather stations of the Crimean peninsula are analyzed. The following climatic indices characterizing the growing season and the ripening period of grapes are calculated: the sum of temperatures above 20 °C, the ratio of the sum of temperatures above 20 °C to the sum of temperatures above 10 °C, the Huglin and Winkler indices, the average temperature of the growing season, the Selyaninov hydrothermal coefficient, the sum of precipitation for the year and the growing season. In addition, the main agroecological factors limiting the possibility and efficiency of growing grapes are considered: the average of the absolute minima of air temperature and the sum of active temperatures above 10 °C. With the help of geoinformation modeling, a digital complex map of the spatial distribution of index data on the analyzed territory is constructed. The distribution of territories in the central part of the Steppe zone of Crimea that are not suitable for planting vineyards is analyzed: with unfavorable soil conditions, with a height of more than 600 m above sea level, with a slope of more than 20 degrees, as well as lands of forest and nature reserves. As a result of a comprehensive analysis of agroecological conditions on the territory of the eastern part of the Steppe zone of Crimea, 10 ampeloecotopes were identified, including: on the territory of the Kirovsky district – 9, Leninsky district – 7. As a result of a comparison of agroecological conditions of selected ampeloecotopes with the requirements of grapevine varieties to growing conditions, taking into account the dependence of quality indicators of viticultural and wine products on agroecological factors recommendations on agroecological optimization of varietal composition and terroir specialization of the viticulture and wine industry in the eastern part of the Steppe zone of Crimea have been developed.

TAFSIR HERMENEUTIKA INTENSIONALISME DALAM PENERAPAN APLIKASI ATLAS

This study aims to determine the meaning of using the Audit Tools and Archives System (ATLAS) application as a financial statement auditing tool, involving Intentional hermeneutics to analyze findings based on historical context, the cultural context in the correlated and explored "text" from which the interpreter tries to interpret the meaning of respective utterances and the language used by the informer utilizing the ATLAS application. Informants in this study include the Managers and Auditor Staff of Thoufan and Rosyid Public Accountants and Partners (Partners) of Achsin Handoko Tomo Public Accounting Firm. The results exhibit that ATLAS presents a complex mapping. The brainchild of ATLAS due to the audit failure cases in Indonesia resulting from a lack of risk assessment/detection in audits has made the Public Accounting Firm implement the ATLAS application. As such, the complexity of the application makes it difficult to implement asthe staffing culture at the Public Accounting Firm causing an imbalance between workload and audit fees for implementing the application.

ROCK2-RNA interaction map reveals multiple biological mechanisms underlying tumor progression in renal cell carcinoma.

Renal cell carcinoma (RCC) is the most common form of kidney cancer in adults. Despite new therapeutic modalities, the outcomes for RCC patients remain unsatisfactory. Rho-associated coiled-coil forming protein kinase 2 (ROCK2) has previously been shown to be upregulated in RCC, and its expression was negatively correlated with patient survival. However, the precise molecular function of ROCK2 has remained unclear. Herein, using RNA-seq analysis of ROCK2 knockdown and control cells, we identified 464 differentially expressed genes, and 1287 alternative splicing events in 786-O RCC cells. Furthermore, mapping of iRIP-seq reads in 786-O cells showed a biased distribution at 5' UTR, intronic and intergenic regions. By comparing ROCK2-regulated alternative splicing and iRIP-seq data, we found 292 overlapping genes that are enriched in multiple tumorigenic pathways. Taken together, our work defined a complex ROCK2-RNA interaction map on a genomic scale in a human RCC cell line, which deepens our understanding of the molecular function of ROCK2 in cancer development.

A scientometric review of the literature on the incorporation of steel fibers in ultra-high-performance concrete with research mapping knowledge

Abstract In the construction industry, the incorporation of steel fibers in ultra-high-performance concrete (UHPC) is vital for improving its mechanical characteristics. In order to identify the essential factors of UHPC, the literature on the effect of steel fibers on UHPC is reviewed using scientometric methods in this work. The review contains complex processes like knowledge mapping, co-occurrence, and co-citation. In order to analyze the bibliographic data on the impact of steel fibers on UHPC, this study makes use of contemporary methodologies for data processing, mining, analysis, presentation, and visualization. The aim is to provide direction for further research in this area by summarizing the literature. In order to achieve this goal, data from the Scopus database, including publication sources, top authors, keywords, significant publications, and nations contributing the most to the subject, are retrieved and examined. According to the scientometric analysis, the most frequently used keyword is “steel fibers,” “Construction and Building Materials” is the most popular publication source in terms of citations and articles, and China is the top-ranking nation in the industry. Academic scholars can gain from this study’s graphical and quantitative portrayal of the contributing researchers and nations by making it easier to share concepts and form collaborative initiatives. This study also shows that steel fibers can improve the mechanical properties of UHPC but their widespread manufacturing and use are dependent on factors including the fiber content and geometry.

Chaotic Complex Hashing: A simple chaotic keyed hash function based on complex quadratic map

In the last two decades, the use of chaotic iterative maps in cryptographic systems, especially chaotic hash functions, has been expanding. Sensitivity to small changes in initial conditions and control parameters in chaotic systems is the best feature for designing a chaotic hash function. This paper introduces a new generalized chaotic map based on a complex quadratic map, which in addition to the chaotic behavior in the real and imaginary parts, also has a high key length, which can guarantee the security of a cryptographic system. Various analyses of dynamical systems, such as the bifurcation diagram and the Lyapunov exponent, show that the proposed chaotic map has the characteristics of a chaotic dynamical system. The foundation of a secure and efficient algorithm for designing and developing a new hash function lies in how to use this new chaotic map. Also, statistical analysis, collision analysis, key space analysis, and speed analysis use to prove the security and efficiency of the proposed method. The results of these analyses and their comparison with similar methods show that the proposed method can be a reliable and efficient method for practical applications in information technology.