bluuebunny/crossref_metadata_2025 huggingface dataset:
VISUALIZATION OF THE FLOWFIELD, ADJOINT PARAMETERS AND HEAT SOURCES AT FLOW STRUCTURE CONTROL
Authors: ALEKSEEV A.K. , BONDAREV A.E.
Published: November 2024

The flowfield control using steady spatially distributed heat sources is addressed with the purpose to diminish the maximum value of the pressure at the surface of body. The two-dimensional inviscid flow around the cylinder is considered as an example for the Edney IV shocks interaction mode. The results for the visualization of the flowfield paramenters, adjoint parameters and heat sources are provided.
THE ROLE OF OBJECT INFORMATION FIELD DENSITY IN GRAPHICAL NEURAL NETWORKS
Authors: BONDAREVA N.A.
Published: November 2024

This paper offers a brief overview of generative neural networks and examines the role of information in learning generative neural networks. In a digital environment, every object is surrounded by a vast information field that includes unordered information and a collection of references about it. The density of an object's information field determines the ability of technologies such as artificial intelligence to recreate its image based on collected data. The more data available, the more accurate and complete the digital image can be recreated. The paper discusses a number of problems that arise in the use of text-to-image networks and possible methods of solving them. The paper considers various aspects of the role of personal data and possible ethical and social implications in the era of generative technologies, as well as the prospects and risks of further development of generative neural networks in specialized fields such as medicine and manufacturing. The rapid development of neural network technologies may have a significant impact on education and social phenomena.
THE USE OF COMPUTER GRAPHICS TOOLS IN THE DESIGN OF SUBWAY LIGHTING
Authors: KAZAKOV D.M. , MAKAROV D.N.
Published: November 2024

The article discusses the use of computer graphics software tools to solve problems in the field of lighting engineering. The authors describe how various functions and capabilities of graphic editors, such as 3D modeling, construction, lighting and visualization, can be applied in the design and analysis of lighting systems. The advantages of using computer graphics in comparison with traditional methods, including improved accuracy, speed and visibility of results, are discussed. Specific examples of the use of graphical tools for solving problems of calculating illumination are given. The article will be of interest to specialists in the field of lighting engineering, architecture and design, as well as developers of computer graphics software.
DEVELOPMENT OF METHODOLOGY FOR VISUALIZATION AND ANALYSIS OF DEFECTS IN ADDITIVE TECHNOLOGIES
Authors: SUVOROV A.V. , TRETYAKOVA O.N. , TUZHILIN D.N. , SHAMORDIN A.A.
Published: November 2024

This paper deals with the issue of visualization and analysis of defects arising in the process of selective laser fusion in order to simplify the selection of technological parameters of the additive manufacturing plant. The paper presents an approach for visualization and detection of defects arising at the stage of flattening of the metal powder layer. The realized approach is able to detect defects at the initial stages of production, which allows to stop the process of printing a known low-quality product. The methodology of hardware-software defect detection is considered and realized. Advantages and disadvantages of the work done and the results obtained are presented.
REGULATORY SUPPORT AND APPLICATION OF DATA VISUALIZATION METHODS
Authors: MAKSIMENKO L.A.
Published: November 2024

The article examines the role and importance of data visualization in the modern information society. The regulatory aspects of the application of the visualization method are considered, including issues of classification, security, confidentiality and ethics of data use. Special attention is paid to the use of visualization techniques to work with open information and open data to present graphs, charts, big data, datasets, dashboards and interactive reports. When performing the work, the ESCD and SPDS standards were taken into account, containing rules and recommendations for the graphic design of objects; BI tools for creating dashboards were considered. At the same time, it is emphasized that modern trends in digitalization and automation put forward additional requirements for information processing, which can be interpreted as a new stage in the field of data visualization.
A NETWORK TECHNOLOGY FOR VISUAL INTERFACES PROGRAMMING
Authors: VASEV P.A.
Published: November 2024

The paper proposes a technology for managing views, such as user interfaces and visualization scenes. The technology is based on network interaction, so it is possible to describe the software components responsible for direct visualization in some languages and libraries, and the general layout and logical parts in others. This makes it possible to launch the project in different environments (web and desktop applications), attract a wider range of developers, and portability of the project between different generations of graphics technologies.
VISUALIZATION OF THE VORTEX STRUCTURES EFFECT ON THE SUPERSONIC FLOW AROUND WING AT AN ATTACK ANGLE
Authors: KONSTANTINOVSKAYA T.V. , BORISOV V.E. , LUTSKY A.E.
Published: November 2024

The effect of vortex structures on the flow around the wing at an attack angle in a supersonic flow is considered in this paper. The results of the analysis and processing of numerical data using scientific identification and visualization methods for vortex flows are presented. The generator wing and the main wing are located at an attack angle of 20° degrees to the incoming flow. Two configurations differing in the length of the vortex generator are considered. The simulation was carried out using URANS equations. Numerical simulations were performed on the K-60 hybrid supercomputer system at the Keldysh Institute of Applied Mathematics of RAS. The scientific visualization of the numerical results was carried out using mainly the Liutex criterion of the identification of vortex structures, which belongs to the third generation of such methods.
USING VISUAL DATA ANALYSIS METHODS TO IDENTIFY THE NEED FOR SEMANTIC DATA INTEGRATION
Authors: CHUPRINA S.I. , GIMASHEVA K.V.
Published: November 2024

The paper proposes an approach based on the use of visual analysis methods to build and improve models of ontology-driven tools of virtual semantic data integration within the framework of Data Fabric technology. This ultimately contributes to an increase in the level of persistence of search results in the case of complex queries involving the presence of multi-subject information resources. The services of the NuCoBoShell tool environment under development allow us to identify whether there are multi-subject information resources among the available resources that satisfy the user's information need, or whether semantic data integration is required and based on the principles of their virtual integration. The data integration at the semantic level is needed because the distribution and heterogeneity of information resources. In our approach, the necessary facts and knowledge are extracted and semantically integrated from of various textual information resources in a unified way. These resources may be not only public but also private accessible within user's local computer. Using ontological models, semantic web methods and visual analysis tools, it is possible to combine heterogeneous data into a single virtual integrated representation of several subject areas at once, regardless of the location of the resources. Generative artificial intelligence tools are used to automate the construction of the ontologies.
APPLICATION OF 3D-PRINTING TECHNOLOGIES IN MANUFACTURING OF TOOLS FOR MICROFORMING OF SHEET METAL BLANKS
Authors: PETROV M.A. , HUNG T.D.
Published: November 2024

The presented paper considers the results of tools' manufacturing for microforming obtained by additive manufacturing or 3D-printing technologies. The method of non-contact structured-light 3D-scanning was chosen as methods for accuracy assessment. It was found out, that not all considered 3D-printing technologies guarantees the matching drawing dimensions, so the tolerances for post-treatment should be taken into consideration. Surface characteristics have been carried out. Repeating the same function follows to loading in cyclic modes even for small batches, that subjected to wear of the tools' surfaces. Based on the tests according to scheme “rod-on-plate”, the wear tendency of the printed samples was determined.
ADDITIVE MANUFACTURING TECHNOLOGY FOR PERSONALIZED DRY ELECTRODE HEADSETS FOR BRAIN-COMPUTER INTERFACES
Authors: CHIRUHIN D.A. , RYABININ K.V.
Published: November 2024

Comfort in wearing and anatomical accuracy of the electrodes head cap play an important role in the organization of brain-computer human-machine interfaces based on electroencephalography. This paper proposes a technological chain and corresponding software tools for a complete cycle of dry electrodes head cap manufacturing for a particular person. The pipeline includes 3D scanning of the head, interactive editing of the electrodes' placement scheme, and automatic generation of a collapsible head cap model optimized for 3D printing. The performance of the pipeline has been validated in practice. The accuracy of electrodes' placement has been evaluated by comparison with the head cap from professional medical equipment and is recognized as sufficient for the tasks of organizing brain-computer interfaces.
A USER-FRIENDLY ONTOLOGY-DRIVEN NEUROINTERFACE INTEGRATION TOOLSET
Authors: LABUTIN I.A. , CHUPRINA S.I.
Published: November 2024

Recently, there has been a remarkable increase in enthusiasm for utilizing neurocomputer interfaces to develop control systems, particularly within the context of various Internet of Things (IoT) ecosystems. Despite this growing interest, integrating these low-level devices and their functional tools with diverse IoT infrastructure components poses significant hurdles. Achieving successful integration demands a deep understanding of both neuroscience and signal processing. To address these complexities, we propose an innovative, ontology-driven framework designed to enable the effortless incorporation of brain-computer interfaces (BCI) into varying IoT environments. By harnessing the principles of ontology engineering, our high-level approach equips researchers and engineers-with varying levels of BCI experience-to automate the integration between neurocomputer interfaces and multiple IoT infrastructures seamlessly. In this paper, we will detail several advancements made to our previous implementation of this strategy. Notable enhancements include the development of an intuitive graphical user interface and the introduction of a new data processing pipeline that utilizes a portable device to validate the effectiveness of our system.
HYBRID ALGORITHMS FOR OBJECT DETECTION IN REAL-TIME COMPUTER VISION SYSTEMS
Authors: VLASOV S.O. , BOGUSLAVSKY A.A.
Published: November 2024

The paper examines the problem of object recognition in photographs using a combined (hybrid) algorithm that combines the classical computer vision method of contour extraction and neural network technologies. A classification of hybrid algorithms is given, and possible structures of the algorithm under study are proposed. A description of the stages of operation of the implemented algorithm and research on a set of test images of a known object is presented. The issue of the efficiency of converting the original image to a contour representation with subsequent search for an object of interest by a convolutional neural network is considered.
THE APPLICATION OF REINFORCEMENT LEARNING METHODS FOR THE TASK OF CONTROLLING A ROBOT MANIPULATOR IN A VIRTUAL ENVIRONMENT
Authors: ZALOGIN N.E. , GRIGORIEV D.S.
Published: November 2024

The development of effective methods for training intelligent agents in tasks involving the control of robotic manipulators in virtual environments is essential for improving the accuracy and efficiency of industrial processes, as well as for further scientific research. This paper focuses on research and improvement of reinforcement learning algorithms, such as Deep Q-Network (DQN) and Proximal Policy Optimization (PPO), for managing agents in the KukaDiverseObjectEnv virtual environment on the PyBullet platform, based on graphical information obtained from the robot's virtual camera. The results showed that the trained agents are capable of solving the given task, and algorithm modifications reduce both training time and the number of required steps. During testing conducted over 1000 episodes, the algorithms demonstrated the ability to control the manipulator. These developments have the potential for industrial applications and further advancement in real-world conditions, highlighting their significance for modern automation and robotics.
OFTWARE TECHNOLOGY FOR MOBILE OBJECT TRACKING BASED ON THE FUSION OF CSRT AND SAM ALGORITHMS
Authors: CAO Y. , BOGUSLAVSKY A.A.
Published: November 2024

At present, a large number of objects tracking algorithms have been developed for video sequences. This paper presents a comparison of tracking algorithms whose implementations are available in the OpenCV library: MOSSE, TLD, KCF, and CSRT. Based on the comparison results using video sequences of urban scenes, the best results were obtained using the CSRT algorithm. However, its direct application presents a typical issue of gradual drift and shrinkage of the tracked region around the object of interest. To address this issue, an improved software technology called CSRT_SAMf is proposed, which offers greater accuracy compared to the CSRT algorithm. In this approach, the Mobile_SAM neural network segmentation model is used for initial estimation of the object's size to prevent the shrinkage of the tracked region, and a speed change parameter is introduced to adjust excessive drift of the tracked region. Additionally, to enhance the robustness of tracking, the proposed software technology integrates the use of the FREAK (Fast Retina Keypoint) feature point extraction algorithm. The results of testing the proposed CSRT_SAMf technology on the UAV123 dataset are presented. The experimental results demonstrate that the proposed CSRT_SAMf technology demonstrates superior performance to the original CSRT algorithm.
FULL BODY SCANNER FOR 3D FIGURINE PRINTING: STATIC AND DYNAMIC APPROACHES
Authors: KRIVOV M.A. , FEDYUKOV M.A. , POSKONIN A.V.
Published: November 2024

Nowadays, depth sensors and 3D printers have become common, affordable and widespread devices. At the same time, there are only a little software solutions for simple and inexpensive fabrication of personalized human figurines. Such statuettes with a total height of 10...20 cm are in demand in the entertainment industry as novel gifts or good complements to classic photographs. In the work, we consider two algorithmic approaches to how such figurines can be easily produced using mass-market depth sensors such as ASUS Xtion PRO and Microsoft Azure Kinect coupled with Raise3D Pro2 and FlashForge Dreamer 3D-printers. The first one is based on the ideas of the classic KinectFusion algorithm and is designed to scan a statically standing person (rigid case). The second way is inspired by the successor algorithm, called DynamicFusion, and works with freely moving people (non-rigid case). After re-implementing and enhancing these classic algorithms, we demonstrate that both approaches have strong and weak sides, so it is worth to use them independently in accordance with the user's needs. The analytical and visual comparison of several figurines produced by these methods are presented as well.
PARAMETRIC REVERSE ENGINEERING OF EXPANDED SHEET METAL PARTS BASED ON SURFACE SKINNING OPERATOR
Authors: SLYADNEV S.E. , VOEVODIN A.M.
Published: November 2024

This study explores a parameterization approach for precise modeling of expanded sheet metal parts. The obtained geometric model is represented as a rectangular grid of "minimal repeatable" patterns. Each pattern is reconstructed using surface skinning techniques based on the laser scan data that is provided by a manufacturing shop. The proposed method enables the generation of accurate and visually realistic geometric models of "minimal repeatable" patterns for various punch tools. Consequently, the shape's parametric model can be subjected to optimization, where the objective function measures the deviation of a laser scan from the nominal shape. The described approach involves creating a number of curve networks and approximating each network using B-spline surfaces. The design parameters exposed by the constructed parametric model possess significant geometric meaning, such as the thickness of the material, the length of the tool, the width of the tool, and so on. Therefore, the exposed variables can be used as meaningful "handles" for design optimization. The results of this study have been incorporated into a commercial software package that generates a variety of expanded metal grids for a range of user-defined parameters.
EXPERIENCE OF IMPLEMENTATION AND ADAPTATION OF AISPOL AND GIS IN FOREST MANAGEMENT
Authors: CHERNYKH L.V. , CHERNYKH D.V.
Published: November 2024

The review of information systems and program complexes of forest inventory information processing is given. The automated information system AISPOL is considered, in which the integration of subsystems with GIS is achieved on the basis of organizational, functional, technical, software and information-linguistic compatibility. The aim of the research is to improve the automation of technological processes related to the collection and presentation of forest data in digital form in forest planning using AISPOL. The basic mathematical models that constitute the core of the control of measured and calculation of calculated indicators on the forest inventory database are developed. The algorithm of automatic construction of thematic forest maps for a forestry or a forest area based on the materials of the database combined with geoinformation has been proposed. It is established that the labor productivity of a specialist on creation of forest thematic maps using AISPOL in comparison with the automated method increases by 25...30 times.
OPTIMIZING THE COMMUNICATION PROCESS OF 3D MODEL DEVELOPERS
Authors: ASYAMOV K.A.
Published: November 2024

The paper deals with the problem of communication of 3D model developers. To solve the problem, a way to optimize communication that reduces time and resource costs was proposed. It was proposed to replace formats that transmit only data about 3D model geometry with the web application transmission format, which frees users from using additional software when visualizing 3D graphics. A justification is given for the use of HTML as a portable format for 3D model data transmission. The structure of HTML-document is extended by adding new elements that allow describing the transferred data about 3D-models.
DESIGN AND DEPLOYMENT OF INTERACTIVE ELECTRONIC TECHNICAL MANUALS WITH AUGMENTED REALITY INTEGRATION FOR ENHANCED PRODUCTION EFFICIENCY
Authors: ERMOLAEVA N.M.
Published: November 2024

Despite significant digitalization and automation of production lines, unique operator knowledge continues to play a crucial role in workshops. Operators provide flexibility and responsiveness in their actions, as well as the ability to autonomously react based on their technical knowledge and experience. Overcoming the gap between modern digital systems for creating and managing information and production workers is a pressing task for both the scientific community and engineers. Developing and implementing a design automation system using interactive electronic technical guidance (IETG) can help solve this problem. One of the modern ways to deliver IETG to operators at the workplace is through the use of augmented reality (AR), which allows for visualizing instructions in the operator's field of vision using digital images, animations, and text prompts. Within the framework of this study, a complex of instrumental tools has been proposed to address the task of preparing IETG and its use in production. Specifically, an original tool has been developed that allows for determining the optimal disassembly sequence of a product and including auxiliary information about the actions performed. In addition, a second tool - an AR application - has been developed to display prepared instructions on a mobile device in the context of the surrounding real environment, for example, in the conditions of a production process. The results can be presented both as IETG on a screen and as an AR application developed for mobile devices. The proposed approach was demonstrated in a prototype of a machine assembly process. It is expected that the presented solutions and approaches will contribute to improving the efficiency and accuracy of the production process.
END-TO-END 3D TECHNOLOGIES AS PART OF A SECURE SOFTWARE PACKAGE "DIGITAL ENTERPRISE FULL LIFE CYCLE SYSTEM" (SARUS)
Authors: GLAZOVA M.A. , ZHUKAEV A.I. , KALINNIKOV I.V. , KIRPICHEV D.A. , ZORINA S.A. , GANCHUK S.N. , TRISHCHENKOV A.V.
Published: November 2024

The main task of modern industry is to create globally competitive and in-demand products of a new generation in the shortest possible time. To successfully solve this problem, it is necessary to constantly generate, apply, accumulate and transfer new knowledge, create and develop high-tech technologies with their subsequent integration into new generation technological chains, develop high-tech innovations and create modern digital industries. In 2016-2023 The Institute of Digital Technologies of the Federal State Unitary Enterprise "RFNC-VNIIEF" has developed a unique domestic import-independent set of programs in a secure version - SRLTS SARUS intended for both enterprises of the military-industrial complex (DIC) and civilian industries. The SRLTS SARUS implements the principle of the end-to-end 3D technology, which is based on the interaction of independent PDM, CAD, CAE projects and CAM within the framework of the “Technological Platform” software module, which is a set of software components designed for construction, operation and integration based on an integrated object-oriented data structure and standard interaction protocols.
PREDICTION AND VISUALIZATION OF TRENDING TOPICS IN BIOMEDICAL IMAGE PROCESSING BASED ON MACHINE LEARNING
Authors: CHARNINE M. , SOMIN N.V.
Published: November 2024

The paper presents a bibliometric and visual analysis of trending topics in the PubMed collection in the field of image processing based on machine learning. The analysis was performed using the PubMed collection of scientific articles, from which 9875 articles were selected with the words “learning” and “image” in the titles. A significant increase (6.29 times over 5 years) in annually published similar articles was revealed. The rating of relevant keywords in the selected articles was calculated and presented. Among the relevant keywords, trending keywords were identified with significant frequencies and increasing trends in the selected articles, as well as with a predicted long-term increase in trends in the PubMed collection. Long-term trend forecast was calculated using the CatBoost machine learning package based on keyword usage in PubMed articles, taking into account citation links. A semantic map of trending keywords is presented, containing information about the novelty and long-term nature of trends. The semantic map was calculated using Word2Vec neural networks and the t-SNE algorithm. Groups of trending keywords that are similar in semantics form trending topics. Similar trending topics are included into clusters on a semantic map. As a result of a visual analysis of the semantic map, eleven trending topics were identified: (1) types of deep learning, (2) self-supervised and few-shot learning, (3) meta-learning and domain adaptation, (4) autoencoder and feature fusion, (5) object and anomaly detection, (6) semantic segmentation, (7) attention mechanism, (8) trending diseases, (9) imaging techniques, (10) personalization and optimization, (11) comparative analysis and reviews. A review of the literature on the most promising trending topics is provided, indicating additional keywords and links to publications.
STUDY OF THE EFFECTIVENESS OF MODERN CONVOLUTIONAL NEURAL NETWORK ARCHITECTURES IN THE TASK OF RECOGNIZING SKIN NEOPLASMS
Authors: MIKHALEV A.S. , ZHUKOVSKAYA V.A. , KOBELEV M.A. , PYATAEVA A.V. , GETZ A.E.
Published: November 2024

The article deals with the problem of increasing incidence of skin cancer, especially melanoma, which is the most aggressive and dangerous form of this disease. The main attention is paid to innovative technologies for diagnosing skin neoplasms, in particular, the use of artificial intelligence. The study analyzes the effectiveness of different convolutional neural network architectures for recognizing skin neoplasms based on digital images. The raw data includes 25331 images of different types of skin lesions from the ISIC 2019 dataset. For training and testing, data augmentation techniques were used to deal with class imbalance. Twenty convolutional neural network models were investigated. The main metrics to evaluate the performance of the models include ROC-AUC, accuracy, precision, recall and F-measure. Experimental results showed that the EfficientNet_v2_s model demonstrated the best performance. Selection of hyperparameters for this model allowed to achieve improvement of metrics: ROC-AUC 0.923, accuracy 0.917, precision 0.833, recall 0.786 and F-measure 0.796. Thus, the use of modern convolutional neural network architectures and machine learning methods can significantly improve the accuracy and reliability of skin neoplasms diagnosis, which is important for early detection and treatment of skin cancer.
STUDY OF THE INFLUENCE OF IMAGE PRE-PROCESSING OPERATIONS ON SEGMENTATION ACCURACY USING CONVOLUTIONAL NEURAL NETWORKS
Authors: IVANOV K.O. , ROZHENCOV A.A. , DUBROVIN V.N.
Published: November 2024

A study was conducted of the influence of various image pre-processing methods on the accuracy of renal tissue segmentation in medical images obtained using a computed tomography. To do this, a number of experiments were carried out to train the U-Net convolutional neural network for kidney tissue segmentation, which differed from each other in the combination of image pre-processing operations, among which we can note a two-level limitation of pixel brightness, randomization of background pixel brightness values, histogram specification and changing the dynamic range of the image by minimax normalization. A quasi-optimal sequence of image preprocessing operations has been established to improve the accuracy of kidney image segmentation using the U-Net convolutional neural network and the stability of its training.
COLOR TRANSFORMATIONS OF VIDEOENDOSCOPIC IMAGES
Authors: OBUKHOVA N.A. , MOTYKO A.A. , POZDEEV A.A. , SAVELIEVA O.R. , YAN X.
Published: November 2024

The paper considers the main procedures of digital processing of endoscopic images aimed at increasing their diagnostic value. It is shown that the existing approaches, solving private problems, lead to the general inconsistency of color transformations in the endoscopic video system. A new multi-objective quality criterion for the synthesis of color transformations, taking into account both the accuracy of color reproduction and the transmission of local color contrast, is proposed. Examples of synthesis of color transformations for target tasks of endoscopic image processing using the proposed criterion are considered.
HISTOLOGICAL IMAGE CLASSIFICATION METHODS BASED ON CONVOLUTIONAL NEURAL NETWORKS WITH GABOR FILTERS
Authors: MURIN E.A. , SOROKIN D.V. , KRYLOV A.S.
Published: November 2024

The article presents histological image classification methods that combine the use of Gabor filters and convolutional neural networks (CNNs). Gabor filters are used to pre-process images to extract frequency characteristics and oriented texture features, improving the efficiency and accuracy of subsequent CNN processing. This approach is aimed at reducing the number of trainable parameters, increasing the learning speed and increasing the adaptive abilities of models, which is especially important when the amount of training data is limited. Various configurations of hybrid networks with Gabor filters of various sizes and their impact on model performance are investigated. Experimental results on the NCT-CRC-HE-100K dataset demonstrate that the proposed methods can achieve high classification accuracy, surpassing traditional CNNs in terms of the number of parameters and learning speed.
SCALE INVARIANCE PROPERTY OF KOLMOGOROV-ARNOLD NETWORKS FOR MRI GIBBS RINGING SUPPRESSION
Authors: PENKIN M.A. , KRYLOV A.S.
Published: November 2024

Gibbs ringing is an artifact in signal and image processing, particularly in scenarios involving reconstruction from sparse or limited data. This paper presents an approach for suppressing Gibbs ringing through the application of a convolutional Kolmogorov-Arnold Network (KAN), a type of artificial neural network inspired by the theory of functional analysis. Our method leverages KANs' capability of reshaping the neural network learning by the stack of non-linear learnable activation functions, derived from the Kolmogorov-Arnold representation theorem, to effectively mitigate oscillatory artifacts. First, we train KANs over the classical solvers: Perona-Malik and Kellner, - thus proving KANs' potential in rediscovering classical deringing algorithms. Second, we examine KANs' scale invariance over the multi-scale testing synthetic dataset, revealing this crucial property of KANs for real-life medical applications. Experiments show a significant reduction in ringing artifacts while preserving valuable image features and overall signal fidelity. The implications of our findings suggest that Kolmogorov-Arnold Networks represent a promising tool for magnetic resonance imaging, enhancing reconstruction quality to a large extent.
ANTIALIASED RENDERING USING BOOLEAN OPERATIONS ON POLYGONS
Authors: BOGOMOLOV K.L. , FROLOV V.A.
Published: November 2024

Antialiasing by increasing the frequency of sampling is limited in precision: it is always possible to find a scene which contains many more triangles than multi-sampling points in some of the pixels. We propose an antialiasing algorithm for polygonal scenes that computes the integral of the picture function over each pixel and considers all visible triangles present in the pixel. The algorithm constructs the scene visible on the screen in a vectorized format using a storage of polygons, and then rasterizes these polygons by mixing colors at each pixel according to the area of intersection of polygon and pixel. An implementation that uses integer arithmetic ensures correct execution and absence of error accumulation even on complex scenes with very small triangles. The determination of visible geometry in a scene is based on using Boolean subtraction of polygons. The present work shows that it is in principle possible to implement rendering with specified properties.
XAI AND WEAK ANNOTATION TOWARD BETTER ACCURACY AND INTERPRETABILITY IN THE NESTED CLASSIFICATION OF BRAIN TUMORS
Authors: REHAMNIA W. , TURLAPOV V.E.
Published: November 2024

Brain tumors are among the most serious and fatal cancers, claiming thousands of lives annually. Early diagnosis, which typically relies on MRI, is crucial for saving lives. Recently, many Artificial Intelligence (AI) techniques have been proposed to alleviate radiologists' workload and expedite diagnosis. Most of these methods utilize deep learning (DL), which, while powerful, can be less reliable and resource-intensive. A significant challenge is the labeling of large and frequently updated biomedical datasets for training DL models. This paper proposes an algorithm that addresses these challenges by leveraging weak annotation and eXplainable AI (XAI). The algorithm also incorporates various image processing steps, such as feature extraction and clustering, to determine both the type and degree of brain tumors. Our study demonstrates state-of-the-art performance, achieving 96% accuracy in the binary classification of Glioma and Meningioma tumors using Random Forest (RF). Additionally, the algorithm provides transparent clustering of Glioma into Low-Grade Glioma (LGG) and High-Grade Glioma (HGG) after type classification. The algorithm is also designed to offer XAI results for explaining DL outcomes and will continue to be developed in this area.
Interpersonal Commitment Scale
Authors: Romya Sharon Immadi  , Sanjana Muthukuri  , Divya Reddy A  , Irine Grace Robin  , Mumtahana Islam
Published: November 2024

The Interpersonal Commitment Scale was constructed to measure the degree of committed behaviors of an individual with their interpersonal relationships; Friendship, Family, and Relationship. The Scale observes three dimensions for the same. The scale is intended for use among the age group of 18-25 years of age. The items were constructed keeping in mind the nature of the young and emerging adults, and statistical procedures were undertaken to establish the Reliability of the scale. The Scale was administered to the above age group (N = 200). The validity of the scale was established through subject expert objective ratings, and the items were adjusted accordingly. The reliability of the scale was established through Cronbach’s Alpha Coefficient. The Reliability scores for each of the dimensions – friendship, family, and romantic relationships – were calculated separately and they are .708, .924, and .904 respectively. The inter-item correlation for all items falls in the range of .4 to .7. The Cronbach’s Alpha Coefficient for the entire scale stands as .823. The scale aims to understand and measure the commitment, as psychology construct, of an individual and his/her relationship with their friends or family, or significant other. The Scale aims to help clinicians and counselors better formulate and personalize the required care and assistance for the individual.
Traumatismo crânio-encefálico e suas implicações no desenvolvimento de hipopituitarismo
Authors: Nery Victor Gabriel Costa Campos de Azevedo , Feitosa Marcus Eduardo Siqueira , Moreira Elidiene de Moura , Pinto Nathalia Oliveira , Araújo Cecília Fernanda Batista de , Carvalho Érica Giovanna Mailho Ismael de , Silva Vanessa Lima do Nascimento , Bezerra Andressa Fernandes , Chianca Ananza Ávila Castelo Branco , Lucena Alinne Beserra de
Published: November 2024

Objetivo: Investigar a relação entre o TCE e o Hipopituitarismo. Métodos: Trata-se de uma revisão integrativa da literatura presente na biblioteca virtual PUBMED e BVS, utilizando os seguintes descritores, em inglês, indexados pelo Decs/Bireme: ''TBI'', ''Hypopituitarism'', ''Pituitary gland''; empregando entre eles o operador booleano AND. Foram encontrados 37 artigos no total, utilizando o filtro de produções científicas dos últimos 5 anos, nos idiomas português, inglês e espanhol. Após a leitura dos artigos, 18 foram excluídos por fugirem à temática evidenciada e duplicidade, e, por fim, 19 trabalhos foram selecionados. Resultados: Os resultados mostraram que sintomas como fadiga, problemas cognitivos, insônia e transtorno de estresse pós-traumático são comuns após TCE leve. A deficiência do hormônio de crescimento (DHC) foi a disfunção hormonal mais prevalente. A apresentação clínica varia conforme o número e tipo de eixos hipofisários afetados, a gravidade da deficiência hormonal e o tempo entre o início do hipopituitarismo e o diagnóstico e tratamento. Considerações finais: Considera-se que é essencial desenvolver protocolos e métodos de triagem para avaliar pacientes após TCE, tanto na fase aguda quanto crônica, e promover estudos contínuos sobre essa relação devido aos potenciais consequências graves para a saúde resultantes do processo neuroendócrino.
Padronização de material técnico em saúde: revisão integrativa
Authors: Tavares Rosa Amélia Durans , Lobato Fernanda do Socorro Carvalho da Silva , Machado Nelma de Jesus Nogueira , Silveira Cinthia Cristina Sousa de Menezes da , Santos Valéria Regina Cavalcante dos
Published: November 2024

Objetivo: Analisar recomendações nacionais a respeito da padronização dos materiais técnicos em saúde Métodos: Neste estudo, foi realizada uma revisão integrativa, que foi escolhida como método devido ao seu rigor e organização na síntese de resultados de pesquisas anteriores sendo composta pelas seguintes etapas: delimitação da questão problema, estabelecimento dos critérios de inclusão e exclusão, coleta de dados, análise de dados e produção dos resultados, sendo utilizadas as bases de dados PubMed, Scopus, Biblioteca Virtual em Saúde, Acervo+ Index base e mecanismo de busca do Google Acadêmico, seguindo os procedimentos metodológicos, sendo: delimitação dos descritores, busca nas bases de dados, aplicação dos critério de inclusão e exclusão e fichamento dos estudos selecionados que foi o total de 7 estudos selecionados  . Resultados: a pesquisa evidencia a relevância da padronização de procedimentos e tecnologias em várias áreas da saúde no sentido de analisar e proporcionar produtos de qualidade que por sua vez refletem positivamente nos serviços de saúde, ademais a padronização de material técnico em saúde não só melhora a qualidade da assistência de saúde, mas também promove a segurança do paciente e a eficiência geral desses serviços. Considerações finais: Pode-se apontar que a padronização dos processos no Núcleo de Avaliação de Tecnologias em Saúde do hospital é um desafio contínuo, que exige o comprometimento de todos os envolvidos e a constante busca por melhorias e a implementação de medidas para aprimorar este processo tem potencial para garantir a excelência no atendimento de saúde.
Osteocartilaginous choristoma of palatine tonsil: A rare entity
Authors: Batra Ashima , Dhingra Shruti , Pujani Mukta , Khandelwal Aparna , Singh Kanika
Published: November 2024

Choristoma is the presence of normal tissue in an abnormal anatomical location. The presence of mature cartilage in the tonsil represents a choristoma as it is not a normal constituent of the tonsil and is a very rare entity. More than 70% of lingual choristomas occur in females; the tongue is the most common site, accounting for 80% of the cases. Osseous choristoma of the tongue is a rather rare entity, with less than 100 cases reported in the literature. We hereby report an osteocartilaginous choristoma of the palatine tonsil in a 42-year-old male patient who presented with a sore throat and difficulty in swallowing, for which he underwent tonsillectomy. Choristoma was an incidental discovery. Histopathology features were consistent with chronic tonsillitis along with incidental occurrence of hyaline cartilage and bone. As choristoma is a benign tumor that usually does not require any further treatment after simple excision, therefore no further treatment was given. The patient is currently under a 2- year follow-up and does not show any signs of recurrence. This case creates awareness about this rare entity among pathologists and clinicians so that overzealous and unnecessary treatment is avoided.
Immunoglobulin superfamily member 1 upregulates myc proto-oncogene to accelerate invasion and metastasis of endometrial cancer: Molecular mechanisms and therapeutic prospects
Authors: Wei Jing , Jiang Jinxiang , Zhang Shuhong , Dong Shuai
Published: November 2024

Objective:

Endometrial cancer (EC) is a common gynecological malignancy, and its metastasis is one of the primary causes of treatment failure. Immunoglobulin superfamily member 1 (IGSF1), a membrane protein, has been associated with the aggressiveness and metastatic capability of various cancers. However, the role and mechanism of this protein in EC remains unclear. Therefore, this study aimed to explore the role of IGSF1 in EC and its possible mechanism.

Material and Methods:

In this study, IGSF1 expression was knocked down through small interfering RNA and short hairpin RNA techniques, and its levels were controlled through overexpression experiments to observe its effects on Ishikawa cells. Wound healing assays, Transwell migration and invasion assays, quantitative real-time polymerase chain reaction, Western blot, and immunofluorescence double labeling were performed to evaluate the ability of cells to migrate, invade, and express markers of the epithelium mesenchymal transition (EMT). In addition, we investigated the regulatory role of IGSF1 in Myc proto-oncogene (c-Myc) expression and its function in lung metastasis through animal models of lung metastasis.

Results:

The results indicate that IGSF1 knockdown inhibited EMT and greatly reduced the invasion ability of Ishikawa cells (P < 0.01). Animal experiments demonstrated that IGSF1 knockdown reduced the number of pulmonary metastatic foci (P < 0.001). On the other hand, IGSF1 overexpression increased Ishikawa cells’ ability to migrate and invade (P < 0.01). IGSF1 overexpression also inhibited E-cadherin expression and promoted that of vimentin (P < 0.001). The expression of c-Myc decreased following IGSF1 knockdown and increased after its overexpression. Silencing of c-Myc reversed the oncogenic effects of IGSF1 (P < 0.01).

Conclusion:

IGSF1 promotes EMT and metastasis in EC through the upregulation of the c-Myc expression. IGSF1 may serve as a potential therapeutic target for EC, and its inhibition can offer new strategies for mitigating the aggressiveness and metastatic potential of this malignancy.
Innovative technique for partial earlobe tear repair using a customized elliptical biopsy punch
Authors: Vetal Akshay Arun , Dhurat Rachita S. , Chethan M. V. , Jain Darshan
Published: November 2024

Incomplete split earlobes, frequently resulting from heavy and pendulous ear jewelry, can cause significant cosmetic and psychological distress. Traditional lobuloplasty techniques often face challenges, particularly in achieving precise and symmetrical results. This study introduces an innovative lobuloplasty technique using a customized elliptical biopsy punch to repair Type I and Type IIA earlobe deformities. By modifying a standard circular biopsy punch, we achieved better margin symmetry and tissue approximation. The procedure involves a two-stage process of stamping and circumduction to excise the defect, followed by closure with vertical mattress sutures. This technique offers several intraoperative advantages, including reduced tissue handling, minimized blood loss, and time efficiency, leading to superior cosmetic outcomes. Our findings suggest that this method is a significant improvement over conventional techniques, providing a more user-friendly approach and enhanced patient satisfaction.
Histopathological array of lesions in nephrectomies with emphasis on immunohistochemical expression of carbonic anhydrase IX in renal cell carcinoma – A 5-year experience in South India
Authors: Medidi Radhika , Gaddam Sampoorna , Duvvuri P. Sindhur Rani , Katta Ramya
Published: November 2024

Objectives:

The present study aimed to assess various pathological entities encountered in nephrectomy specimens received in our tertiary care teaching hospital in South India to assess the immunohistochemical expression of carbonic anhydrase IX (CA IX) in various subtypes of renal cell carcinomas (RCCs), and to evaluate its usefulness as a diagnostic and prognostic marker in RCCs.

Materials and Methods:

The present study was a 5-year retrospective study performed in a teaching hospital. All nephrectomy specimens were routinely fixed, grossed, processed, and sectioned for histopathological evaluation. Immunohistochemistry for CA IX expression was performed manually in all cases diagnosed as RCCs.

Statistical analysis:

All data were tabulated in Microsoft Excel 2020, and means and standard deviations were calculated using the same.

Results:

A total of 102 patients were included in the study, with the most common age group being the fifth decade of life and female preponderance. CA IX expression was observed in 100% of clear cell carcinomas, and staining intensity varied with the nuclear grade of the tumor.

Conclusions:

Non-neoplastic lesions were the most common cause of nephrectomy in our study region. Clear cell RCC is associated with the highest expression of CA IX and seems to be associated with lower nuclear grade and lower T stage; hence, it may serve as a prognostic marker for such cases.
Retinal vasculitis – Current approach to diagnosis, investigations, and management
Authors: Biswas Jyotirmay , Mathew Namitha Rachel
Published: November 2024

Retinal vasculitis is defined as the inflammation of the retinal vessel wall, which may involve the veins (periphlebitis), arteries (periarteritis), capillaries (capillaritis), or a combination of these. It is an uncommon sight-threatening retinal vascular inflammatory disorder resulting in a plethora of clinical features. It may be associated with systemic inflammatory conditions, infections, neoplastic diseases, or may be idiopathic. Reaching a diagnostic etiology for retinal vasculitis is often a diagnostic challenge. Meticulous examination, essential laboratory investigations, fundus photography, autofluorescence, fundus fluorescein angiography, indocyanine green angiography, optical coherence tomography (OCT), OCT angiography, B scan ultrasonography, and widefield fundus imaging enable us to arrive at a diagnosis. Antivascular endothelial growth factor and laser photocoagulation help to arrest neovascularization. Newer agents, such as immunomodulators and biologics, are effective against these sight-threatening conditions. Early management often helps to salvage vision and minimize comorbidities in these conditions. This review highlights on diagnosis and management of retinal vasculitis.
Pulmonary graphics – An insight into newborn lung on ventilator
Authors: Venkatesh H. A. , Venkatesh Swathi
Published: November 2024

Neonatal care with technology has brought down mortality and morbidity in the world. More and more pre-term neonates are seeing the world with a quality life. Advanced software is used in the ventilators to check the breath-to-breath variability in the care of sick neonates. The anatomical and physiological aspects of a neonatal lung are essential before understanding and analysing the waves on the monitor. Constant monitoring of both the baby and the waves of lung mechanics is essential in clinical decision-making. Having a sophisticated machine with the graphics of lung mechanics is of no use if the clinician is incapable of correctly interpreting the waves. The pulmonary graphics is the graphical representation of the lung similar to the electrocardiogram and electroencephalogram routinely used to know the physiology of the heart and brain. With this background, the pulmonary graphics are dealt with simply, and therefore, the reader can understand the pulmonary graph well and use it efficiently in the care of sick neonates. The incorporation of microprocessors and sensors into the ventilators has made the clinician monitor lung function continuously in real time. The three basic parameters of the respiratory system – the pressure, the flow, and the volume – are visualised online. This can be utilised along with the clinical data, the blood gas, and the chest Roentgenogram.