Transformation Tasks Research Articles

Revealing the different levels of action monitoring in visuomotor transformation task: Evidence from decomposition of cortical potentials.

This study investigates the cortical correlates of motor response control and monitoring, using the Theory of Event Coding (TEC)as a framework to investigate signals related to low-level sensory processing of motor reafference and high-level response monitoring, including verification of response outcomes with the internal model. We used a visuomotor paradigm with two targets at different distances from the participant. For the recorded movement-related cortical potentials (MRCPs), we analyzed their different components and assessed the movement phases during which they are active. Residual iteration decomposition (RIDE) and multivariate pattern analysis (MVPA) were used for this analysis. Using RIDE, we separated MRCPs into signals related to different parallel processes of visuomotor transformation: stimulus processing (S-cluster), motor response preparation and execution (R-cluster), and intermediate processes (C-cluster). We revealed sequential activation in the R-cluster, with execution-related negative components and positive contralateral peaks reflecting reafference processing. We also identified the motor post-imperative negative variation within the R-cluster, highlighting the response outcome evaluation process included in the action file. Our findings extend the understanding of C-cluster signals, typically associated with stimulus-response mapping, by demonstrating C-activation from the preparatory stages through to response termination, highlighting its participation in action monitoring. In addition, we highlighted the ability of MVPA to identify movement-related attribute encoding: where statistical analysis showed independence of stimulus processing activity from movement distance, MVPA revealed distance-related differences in the S-cluster within a time window aligned with the lateralized readiness potential (LRP). This highlights the importance of integrating RIDE and MVPA to uncover the intricate neural dynamics of motor control, sensory integration, and response monitoring.

Research on the Impact of Enterprise Digital Transformation on High-Quality Development and Countermeasures

With the rapid development of the digital economy, enterprises face the important task of digital transformation. This paper, based on the analysis of literature, discusses the positive impacts of digital transformation on the high-quality development of enterprises, reveals the main mechanisms of digital transformation, and proposes corresponding countermeasures for the challenges encountered by enterprises during the digital transformation process. The study finds that digital transformation can optimize the talent structure of enterprises, improve organizational governance, nurture new market environments, and thereby promote the high-quality development of enterprises. This paper suggests that enterprises should strengthen the training of digital talents, optimize organizational structures, and innovate business models using digital technologies to adapt to the needs of the digital age.

Stain transformation using Mueller matrix guided generative adversarial networks.

Recently, virtual staining techniques have attracted more and more attention, which can help bypass the chemical staining process of traditional histopathological examination, saving time and resources. Meanwhile, as an emerging tool to characterize specific tissue structures in a label-free manner, the Mueller matrix microscopy can supplement more structural information that may not be apparent in bright-field images. In this Letter, we propose the Mueller matrix guided generative adversarial networks (MMG-GAN). By integrating polarization information provided by the Mueller matrix microscopy, the MMG-GAN enables the effective transformation of input H&E-stained images into corresponding Masson trichrome (MT)-stained images. The experimental results demonstrate the accuracy of the generated images by MMG-GAN and reveal the potential for more stain transformation tasks by incorporating the Mueller matrix polarization information, laying the foundation for future polarimetry-assisted digital pathology.

This is the Table I Want! Interactive Data Transformation on Desktop and in Virtual Reality.

Data transformation is an essential step in data science. While experts primarily use programming to transform their data, there is an increasing need to support non-programmers with user interface-based tools. With the rapid development in interaction techniques and computing environments, we report our empirical findings about the effects of interaction techniques and environments on performing data transformation tasks. Specifically, we studied the potential benefits of direct interaction and virtual reality (VR) for data transformation. We compared gesture interaction versus a standard WIMP user interface, each on the desktop and in VR. With the tested data and tasks, we found time performance was similar between desktop and VR. Meanwhile, VR demonstrates preliminary evidence to better support provenance and sense-making throughout the data transformation process. Our exploration of performing data transformation in VR also provides initial affirmation for enabling an iterative and fully immersive data science workflow.

Adaptive Factor Fuzzy Controller for Keeping Multi-UAV Formation While Avoiding Dynamic Obstacles

The development of unmanned aerial vehicle (UAV) formation systems has brought significant advantages across various fields. However, formation change and obstacle avoidance control have long been fundamental challenges in formation flight research, with the majority of studies concentrating primarily on quadrotor formations. This paper introduces a novel approach, proposing a new method for designing a formation adaptive factor fuzzy controller (AFFC) and an artificial potential field (APF) method based on an enhanced repulsive potential function. These methods aim to ensure the smooth completion of fixed-wing formation flight tasks in three-dimensional (3D) dynamic environments. Compared to the traditional fuzzy controller (FC), this approach introduces a fuzzy adaptive factor and establishes fuzzy rules to address parameter-tuning uncertainties. Simultaneously, improvements to the obstacle avoidance algorithm mitigate the issue of local optimal values. Finally, multiple simulation experiments were conducted. The findings show that the suggested method outperforms the proportional–integral–derivative (PID) control and fuzzy control methods in achieving formation transformation tasks, resolving formation obstacle avoidance challenges, enabling formation reconstruction, and enhancing formation safety and robustness.

Value-led participatory design approach for improving public health clinic services

IMPACT This study details how to drive transformative collaboration with a health bureau to implement transformative tasks in public health clinic (PHC) using service design. Value-led participatory design is adopted to identify and address key challenges, enhance decision-making processes, and generate a new elevation model for public health service delivery. The article highlights the importance of continuous evaluation and adaptation of services based on stakeholder feedback and evolving community needs, emphasising the dynamic nature of healthcare service improvement. The insights gained from this collaboration provide practical solutions for common challenges faced by public health systems in various contexts.

A Concrete Syntax Transformation Approach for Software Language Processing

In this paper we present an approach for software language processing tasks such as code generation, reverse-engineering and refactoring, based upon text-to-text (T2T) transformations expressed using the concrete syntax of the source and target software languages. The goal of the approach is to provide simpler and more usable techniques for specifying such tasks, compared to model-to-model (M2M) or model-to-text (M2T) transformation approaches. We evaluate the approach on language processing tasks of domain-specific language (DSL) tool support, software abstraction, model transformation, reverse engineering and program translation, and show that it can be effective for these tasks.

Building Three-dimensional Virtual Historic Fashion Museum Exhibitions: From the Perspective of Technology Affordances

Museums are currently undertaking the task of digital transformation. Transformational technology generates revitalization of the curatorship, cultural heritage presentation, management model, and traditional roles of museums. The creation of three-dimensional (3D) virtual museum exhibitions is important to fulfill the revolutionary operational requirements and projections of recent museums through digital transformation. The objectives of this project were to (1) create realistic 3D virtual museum exhibitions accessible from the web, focusing on historic fashions, and (2) provide an analysis of the process and resources for creating 3D virtual museum exhibitions featuring object-focused exhibits. As a theoretical background of this project, the theory of technology affordances and the affordance actualization process were applied in the creation of 3D virtual museum exhibitions. The results of this project provide cultural heritage museums and institutions with useful precedents for the development of 3D virtual historic fashion museum exhibitions.

ТЕНДЕНЦИИ И ПЕРСПЕКТИВЫ РАЗВИТИЯ ЦИФРОВОЙ ТРАНСФОРМАЦИИ В УПРАВЛЕНИИ ДЕЯТЕЛЬНОСТЬЮ ПРЕДПРИЯТИЙ АГРОПРОМЫШЛЕННОГО КОМПЛЕКСА РОССИИ

The scientific article presents an assessment of the current state and potential of digital transformation of enterprises of the agro-industrial complex of Russia. The relevance of the research is related to the general trend of digitalization and the spread of digital technologies that improve production, management and business processes in organizations of various spheres and sectors of the Russian and global economy. The object of the study is the enterprises of the agro-industrial complex of Russia. The subject is the technology of digital transformation of Russian agricultural enterprises. A review of digital technologies in management and agricultural production has been conducted. The measures aimed at ensuring the economic sustainability of Russian agricultural enterprises in the process of solving the tasks of digital transformation are proposed.

Keywords-based conditional image transformation

In recent years, Generative Adversarial Networks (GANs) and their variants, such as pix2pix, have occupied a significant position in the field of image generation. Despite the impressive performance of the pix2pix model in image-to-image transformation tasks, its reliance on a large amount of paired training data and computational resources has posed a crucial constraint to its broader application. To address these issues, this paper introduces a novel algorithm, Keywords-Based Conditional Image Transformation (KB-CIT). KB-CIT dynamically extracts keywords from the input grayscale images to acquire and generate training data, thus avoiding the need for a large amount of paired data and significantly improving the efficiency of image transformation. Experimental results demonstrate that KB-CIT performs remarkably well in image colorization tasks and can generate high-quality colored images even with limited training data. This algorithm not only simplifies the data collection process but also exhibits significant advantages in terms of computational resource requirements, data utilization efficiency, and personalized real-time training of the model, thereby providing new possibilities for the widespread application of the pix2pix model.

Standardization of ultrasound images across various centers: M2O-DiffGAN bridging the gaps among unpaired multi-domain ultrasound images

Domain shift problem is commonplace for ultrasound image analysis due to difference imaging setting and diverse medical centers, which lead to poor generalizability of deep learning-based methods. Multi-Source Domain Transformation (MSDT) provides a promising way to tackle the performance degeneration caused by the domain shift, which is more practical and challenging compared to conventional single-source transformation tasks. An effective unsupervised domain combination strategy is highly required to handle multiple domains without annotations. Fidelity and quality of generated images are also important to ensure the accuracy of computer-aided diagnosis. However, existing MSDT approaches underperform in above two areas. In this paper, an efficient domain transformation model named M2O-DiffGAN is introduced to achieve a unified mapping from multiple unlabeled source domains to the target domain. A cycle-consistent “many-to-one” adversarial learning architecture is introduced to model various unlabeled domains jointly. A condition adversarial diffusion process is employed to generate images with high-fidelity, combining an adversarial projector to capture reverse transition probabilities over large step sizes for accelerating sampling. Considering the limited perceptual information of ultrasound images, an ultrasound-specific content loss helps to capture more perceptual features for synthesizing high-quality ultrasound images. Massive comparisons on six clinical datasets covering thyroid, carotid and breast demonstrate the superiority of the M2O-DiffGAN in the performance of bridging the domain gaps and enlarging the generalization of downstream analysis methods compared to state-of-the-art algorithms. It improves the mean MI, Bhattacharyya Coefficient, dice and IoU assessments by 0.390, 0.120, 0.245 and 0.250, presenting promising clinical applications.

Towards achieving the sustainable development goals: a collaborative action plan leveraging the circular economy potentials

This contribution to the journal “Gruppe. Interaktion. Organisation. (GIO)” delves into the critical role of Sustainable Development Goal 17 (SDG 17), “Partnership for the Goals,” in fostering interdisciplinary collaboration to further circular economy objectives. Aiming to address the existing research focus on isolated technical aspects within the circular economy, this study uses an expertise- and interaction-based foresight process to integrate perspectives from business, engineering, social sciences, and work and organizational psychology to unearth broader, interconnected challenges and solutions for the implementation of circular economy practices. Based on the pooled experience of experts within the foresight process, this contribution elucidates major challenges, ongoing issues, and prospective hurdles to be tackled by 2030 in circular economy, presenting an action plan centered on interdisciplinary cooperation and stakeholder engagement to advance labor conditions and continuous learning, sustainable and regenerative systems, minimize waste, and optimize resource efficiency. The collaborative action plan serves as a pivotal resource for the transformation task for researchers and practitioners, offers insights and strategic directions for implementing circular economy practices, and emphasizes collective responsibility and action in achieving global sustainability, all while aligning with the principles of SDG 17. The presented collaborative approach propels the discourse on sustainability forward, highlighting the potential of the circular economy in realizing a more sustainable world by 2030.

Educational models and technologies in the era of digital transformation

At present digital transformation of the society faces the problem of a shortage of a highly qualified personnel - specialists in the field of the latest information technologies, intellectual scientists with a high-quality fundamental education. The solution to this problem lies in the introduction of new educational models and technologies. The purpose of the research is to study the strategy for the formation of a new conceptual scheme of modern education. It has been emphasized that two leading educational models are currently being successfully implemented and complement each other: the classical model of «completed» education with the basic principle of «education once and for life», covering the need of the society for the generation and dissemination of knowledge, as well as the storage of cultural ideals, and the second model, called the «lifelong education model», which meets the principle of «lifelong education», corresponding to the rapid changes in technology and the nature of digital transformations of the society. The article pays special attention to new educational technologies such as: 1) analytical technologies, which are based on the analysis of big data from educational institutions in real time; 2) adaptive (or intellectual) learning, which is based on the principles of personalization of learning and building an individual educational trajectory; 3) Smart education, using learning tools in an interactive educational environment with elements of distance and mobile education. The methodological basis of the research is a systematic approach and general methods of scientific knowledge, such as analysis, synthesis, generalization. The relevance of the topic is associated with increased attention to the problem of matching the quality of the Russian education with the promising tasks of the digital transformation of the Russian society. Key conclusion. A high professional level of the personnel reserve, which will be able to practically implement state digitalization programs, is possible and is associated with the construction of a new concept of modern education.

Prospects and challenges of digital transformation of the general education system in the Russian Federation

The paper is devoted to the urgent problem of increasing the effectiveness of digital transformation mechanisms in the sphere of general education, aimed at improving the efficiency of functioning of general educational organizations. The analysis of normative legal acts regulating state regulation in the field of information technology application in education, domestic and foreign literature devoted to digital transformation of the economy and society as a whole has been carried out. The main directions of digital transformation of education were analyzed. The lack of elaboration of the issues of digital transformation of general education along with a large number of publications related to higher education institutions is noted. The main technological transformations preceding the current stage of introducing end-to-end technologies in the sphere of general education in the Russian Federation are highlighted. Emphasis is placed on the necessity of digital transformation of general education management. The problems of introducing end-to-end technologies in the sphere of general education management are considered against the background of the acute need to master new technologies and the transition of the economy to a new stage of development. The tasks of digital transformation of education have been studied and the analysis of the reasons hindering the introduction of modern digital technologies has been carried out, which allowed us to identify the need to update not only the methods of conducting the educational process with the use of digital educational content, but also to qualitatively change the management system of a modern educational organization. The study showed that the digital transformation of general education cannot take place without state regulation and research in the field of correlation between the classroom and digital component. Recommendations on the implementation of projects in the system of general education are given, which allow to eliminate the duplication of management functions, reduce the cost of software development and implementation at different levels of education management.

Digitalization as a determinant of transformation of the real sector of the economy of the macroregion (using the example of the North Caucasus Federal District)

Purpose: is to study of the processes of digitalization and digital transformation of the real sector of the economy of the regions of the North Caucasus Federal District. Methods: the methodological basis of the study was the concept of the digital economy, the theoretical principles of supply-side economics, the systems approach, trend analysis and predictive analytics. The study is based on the use of the methods of economic and statistical analysis, scientifi c abstraction, analogies and scientifi c generalizations. The methods used are characterized by validity and show a high degree of eff ectiveness. Results: digitalization and digital transformation processes are underway in the North Caucasus Federal District, but the pace remains low. To accelerate these processes, it is necessary to solve two interrelated problems: fi rstly, to materialize the processes of digitalization and digital transformation in the real sector of the economy of the regions of the federal district, and secondly, to train personnel in certain specialties who can eff ectively operate digital technologies. In the fi rst case, it is possible to use the model of catch-up development at the regional level, which will make it possible to implement the principle of “advantage of backwardness” and use the accumulated global and regional experience in the transition to the modern trends in the operation of digital technologies. In the second case, it is proposed to organize special centers in the subjects of the district for retraining digital technologies specialists with the necessary competencies and/or advanced training with the issuance of the confi rming certifi cates. Such centers could train exclusive specialists at the request of enterprises or engage in refresher training and retraining of the necessary specialists. The creation of the centers is possible on the basis of public-private partnership. Conclusions and Relevance: the main task of the digital transformation of industry is considered to be the modernization of production process management, which will lead to the signifi cant increase in labor productivity. To implement such a scenario, the economic entities in the regions of the North Caucasus Federal District need to move away from the traditionalist approaches that take place in the organization and management of enterprises, and switch to the processes of digitalization and digital transformation of the real sector of the economy of the district.

Экосистема как механизм государственно- частного партнерства

This very study considers the background and possibilities of implementation ecosystem in the governmental toolbar for the strategic projects. 
 The urgency of the problem is caused by the list of factors, including:
 - negative external background, affecting the availability of resources, technologies and specialists for the implementation of transformation tasks;
 - lack of socio-economic institutes which are ready to ensure the realization strategic goals at the operational level;
 - the need for rapid restructuring of the national economy, which can be provided through mechanisms of operational interaction between the government, business and the population.
 Most modern studies don’t analyze ecosystems as a tool for the supporting of strategic goals of the national economy.
 The purpose of the study is to identify opportunities and risks for the government and society while using ecosystems in realization strategic state goals. 
 The purpose of the study predetermined the following tasks:
 - Determination of the impact of negative external factors of the transformation of the national economy.
 - The role and functions of ecosystems in the implementation of strategic objectives of the national economy.
 - Scenarios and risks of ecosystem impact growth.
 The following tools are used in the study: structural and institutional analyze, modeling and forecasting. The ecosystem is considered as a complex integration platform that unites consumers and producers into a single system through end-to-end sales channels, a single financial infrastructure and communication standards. As the best practices of interaction between ecosystems and the state, the experience of implementing complex projects of the largest national ecosystems was used: Sber, MTS, Rostelecom, Yandex.
 The paper proposes the current scheme of interaction between the ecosystem and the government in the framework of the realization strategic transformation programs. The scheme is formed on the basis of a sophisticated business model (B2G2B2C), involving the participation of all macroeconomic agents. The scheme presents several functional contours: the formation and execution of a complex regional order (the essential contour of agent interaction), financial interaction between participants.
 The second part of the study examines scenarios for the development of the relationship between the ecosystem and the state from the position of influence on society, taking into account two variables: the willingness of the state to play an active role in regulating the activities of ecosystems within the national contour; the level of favorability of external rejection for ecosystems. As a result, 4 scenarios were considered that answer the questions of ecosystem development, their contribution to public welfare, and work with innovations.

Leveraging Cloud-Native Architectures for Enhanced Data Wrangling Efficiency: A Security and Performance Perspective

In the contemporary landscape of big data analytics, cloud computing environments have emerged as pivotal platforms for data-wrangling processes, catering to the ingestion and transformation of vast datasets. This research paper explores optimization strategies for data wrangling within cloud computing environments, a critical component in the realm of big data analytics. It addresses the significant security and performance challenges encountered during data pipeline execution in cloud platforms. By proposing a novel strategy that includes executing data pipelines within a customer's Virtual Private Cloud (VPC) and employing pushdown optimization for data transformation tasks in cloud data warehouses and databases, this approach seeks to enhance security and performance. The paper examines the theoretical underpinnings and practical applications of these strategies, conducting a comparative analysis with traditional data-wrangling methods to underscore the benefits of performance and security. Additionally, it assesses the implications of this approach on cost, scalability, and manageability within cloud architectures. The findings offer valuable insights and recommendations for deploying these optimization techniques in practical scenarios, setting the stage for future research in refining data-wrangling practices in cloud environments.

ANALYSING THE PROCESSES OF DIGITAL TRANSFORMATION OF THE EDUCATIONAL ENVIRONMENT THROUGH THE EXAMPLE OF A RUSSIAN UNIVERSITY

Abstract. The COVID-19 pandemic contributed to the forced digitalisation of all spheres of society and exposed the political and economic prerequisites for its further development. The government motivates universities to develop digital educational products and create their own digital educational environment both independently and in cooperation with other universities and EdTech companies. The article discusses different tasks of the digital transformation of higher education in the European Union and Russia, focuses on the development of the market of commercial educational programmes presented by EdTech companies, and describes the benefits and risks of digitalisation. As an illustrative example, the authors take a detailed look at the digital educational environment of one of the leading Russian universities, the development and implementation of digital educational and administrative platforms to simplify the learning process. In order to assess the advantages and disadvantages of digitalisation of education, a survey of university students was conducted, which made it possible to identify their attitude to the innovations and give them an assessment.

Full life cycle emission reduction potential of ultra-low emission transformation in China's cement industry

China accounts for more than 50% of the global total cement production, the emission of pollutants in the cement industry occupies a large proportion of the industries. Some provinces have first carried out in-depth treatment of the cement industry, and the national level will also introduce an implementation plan for ultra-low emission transformation of the cement industry to promote continuous improvement of China's air quality. In this work, a pollutant emission inventory covering the full life cycle of the cement industry, including organized emission, unorganized emission and transportation, was established based on pollutant discharge permit, Continuous Emission Monitoring System (CEMS) database and field investigation. And, the emission reduction potential of particulate matter (PM), sulfur dioxide (SO2) and nitrogen oxide (NOx) after the implementation of ultra-low emission transformation in cement industry was evaluated. The results show that the existing dedusting, desulphurization and denitration technologies can control the concentrations of PM, SO2 and NOx below 10 mg/m3, 35 mg/m3 and 50 mg/m3, respectively. The emission reduction potential of PM, SO2 and NOx in cement industry is 259.54 kt, 14.98 kt and 607.04 kt, corresponding emission reduction ratio is 37%, 24% and 64%, respectively. In addition, this work reveals the spatial characteristics of pollutant emission level and emission reduction potential of the cement industry, which is conducive to the rational layout of ultra-low emission transformation, and push forward the transformation task by area and stage.

A clinical 3D pointing test differentiates spatial memory deficits in dementia and bilateral vestibular failure

BackgroundDeficits in spatial memory, orientation, and navigation are often neglected early signs of cognitive impairment or loss of vestibular function. Real-world navigation tests require complex setups. In contrast, simple pointing at targets in a three-dimensional environment is a basic sensorimotor ability which provides an alternative measure of spatial orientation and memory at bedside. The aim of this study was to test the reliability of a previously established 3D-Real-World Pointing Test (3D-RWPT) in patients with cognitive impairment due to different neurodegenerative disorders, bilateral vestibulopathy, or a combination of both compared to healthy participants.MethodsThe 3D-RWPT was performed using a static array of targets in front of the seated participant before and, as a transformation task, after a 90-degree body rotation around the yaw-axis. Three groups of patients were enrolled: (1) chronic bilateral vestibulopathy (BVP) with normal cognition (n = 32), (2) cognitive impairment with normal vestibular function (n = 28), and (3) combined BVP and cognitive impairment (n = 9). The control group consisted of age-matched participants (HP) without cognitive and vestibular deficits (n = 67). Analyses focused on paradigm-specific mean angular deviation of pointing in the azimuth (horizontal) and polar (vertical) spatial planes, of the preferred pointing strategy (egocentric or allocentric), and the resulting shape configuration of the pointing array relative to the stimulus array. Statistical analysis was performed using age-corrected ANCOVA-testing with Bonferroni correction and correlation analysis using Spearman’s rho.ResultsPatients with cognitive impairment employed more egocentric pointing strategies while patients with BVP but normal cognition and HP used more world-based solutions (pBonf 5.78 × 10-3**). Differences in pointing accuracy were only found in the azimuth plane, unveiling unique patterns where patients with cognitive impairment showed decreased accuracy in the transformation tasks of the 3D-RWPT (pBonf < 0.001***) while patients with BVP struggled in the post-rotation tasks (pBonf < 0.001***). Overall azimuth pointing performance was still adequate in some patients with BVP but significantly decreased when combined with a cognitive deficit.ConclusionThe 3D-RWPT provides a simple and fast measure of spatial orientation and memory. Cognitive impairment often led to a shift from world-based allocentric pointing strategy to an egocentric performance with less azimuth accuracy compared to age-matched controls. This supports the view that cognitive deficits hinder the mental buildup of the stimulus pattern represented as a geometrical form. Vestibular hypofunction negatively affected spatial memory and pointing performance in the azimuth plane. The most severe spatial impairments (angular deviation, figure frame configuration) were found in patients with combined cognitive and vestibular deficits.