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Ivannikov Memorial Workshop (IVMEM)

作者： Bugerya, Alexander Borisovich Kulagin, Ivan Ivanovich Padaryan, Vartan Andronikovich Solovev, Mikhail Aleksandrovich Tikhonov, Andrei Yur'evich Russian Acad Sci Keldysh Inst Appl Math Moscow Russia Russian Acad Sci Ivannikov Inst Syst Programming Moscow Russia Lomonosov Moscow State Univ Moscow Russia

ISBN: (纸本)9781728146232

One of the tasks of binary code security analysis is detection of undocumented features in software. This task is hard to automate, and it requires participation of a cybersecurity expert. The way of representation of the algorithm under analysis strongly determines the analysis effort and quality of its results. Existing intermediate representations and languages are intended for use in software that either carries out optimizing transformations or analyzes binary code. Such representations and intermediate languages are unsuitable for manual data flow analysis. This paper proposes a high-level hierarchical flowchart-based representation of a program algorithm as well as an algorithm for its construction. The proposed representation is based on a hypergraph and it allows both automatic and manual data flow analysis on different detail levels. The hypergraph nodes represent functions. Every node contains a set of other nodes which are fragments. The fragment is a linear sequence of instructions that does not contain call and ret instructions. Edges represent data flows between nodes and correspond to memory buffers and registers. In the future this representation can be used to implement automatic analysis algorithms. An approach is proposed to increasing quality of the developed algorithm representation using grouping of single data flows into one flow connecting logical algorithm modules.

关键词： flowcharts intermediate representation binary code analysis data flow analysis

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Visualization of Complex Industrial Products and Processes Using Hierarchical Dynamic LODs 26

Visualization of Complex Industrial Products and Processes U...

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26th ISTE International Conference on Transdisciplinary Engineering

作者： Semenov, Vitaly Shutkin, Vasily Zolotov, Vladislav Russian Acad Sci Ivannikov Inst Syst Programming Moscow Russia State Univ Moscow Inst Phys & Technol Moscow Russia State Univ Higher Scool Econ Moscow Russia

ISBN: (纸本)9781643680217;9781643680200

Visualization of complex industrial products and processes is a challenging problem connected with emerging collaborative environments and integrated product development technologies. Due to the large number of components and the complexity of their geometrical models, direct display of products and processes by current graphics systems at reasonable frame rates becomes impossible. One of the promising approaches to visualization of complex scenes is a simplification of polygonal models often hidden under the term level of details (LOD). Nowadays, different techniques, including hierarchical level of details (HLOD), are widely employed for visualization of large scenes by means of the geometry simplification and representation of entire groups of objects. However, both LOD and HLOD techniques face dramatic difficulties when scenes undergo modifications. Known attempts to adapt techniques for dynamic scenes did not result in significant progress. In the paper we present a concept of hierarchical dynamic level of details (HDLOD) and prove its feasibility and applicability to deterministic pseudo-dynamic scenes. Such scenes arise in various problems connected with visual modeling of complex construction projects, city infrastructure programs, and machinery assembly production. The results of computational experiments confirm the prospects of the introduced HDLODs and proposed complementary method for their automatic generation and application in industrial practice.

关键词： Product and Process Modeling Visualization Level of Details

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Multi-objective Configuration of a Secured Distributed Cloud Data Storage 6th

Multi-objective Configuration of a Secured Distributed Cloud...

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6th Latin American Conference on High Performance Computing (CARLA)

作者： Enrique Garcia-Hernandez, Luis Tchernykh, Andrei Miranda-Lopez, Vanessa Babenko, Mikhail Avetisyan, Arutyun Rivera-Rodriguez, Raul Radchenko, Gleb Jaime Barrios-Hernandez, Carlos Castro, Harold Drozdov, Alexander Yu CICESE Res Ctr Ensenada 22860 Baja California Mexico North Caucasus Fed Univ Stavropol 355009 Russia RAS Ivannikov Inst Syst Programming Moscow 109004 Russia South Ural State Univ Chelyabinsk 454080 Russia Univ Ind Santander Bucaramanga Colombia Univ Los Andes Bogota Colombia State Univ Moscow Inst Phys & Technol Moscow Russia

ISBN: (纸本)9783030410056;9783030410049

Cloud storage is one of the most popular models of cloud computing. It benefits from a shared set of configurable resources without limitations of local data storage infrastructures. However, it brings several cybersecurity issues. In this work, we address the methods of mitigating risks of confidentiality, integrity, availability, information leakage associated with the information loss/change, technical failures, and denial of access. We rely on a configurable secret sharing scheme and error correction codes based on the Redundant Residue Number system (RRNS). To dynamically configure RRNS parameters to cope with different objective preferences, workloads, and cloud properties, we take into account several conflicting objectives: probability of information loss/change, extraction time, and data redundancy. We propose an approach based on a genetic algorithm that is effective for multi-objective optimization. We implement NSGA-II, SPEA2, and MOCell, using the JMetal 5.6 framework. We provide their experimental analysis using eleven real data cloud storage providers. We show that MOCell algorithm demonstrates best results obtaining a better Pareto optimal front approximation and quality indicators such as inverted generational distance, additive epsilon indicator, and hypervolume. We conclude that multi-objective genetic algorithms could be efficiently used for storage optimization and adaptation in a non-stationary multi-cloud environment.

关键词： Cloud storage Multi-objective optimization Genetic algorithm

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Immunometabolism at the crossroads of obesity and cancer-a Keystone Symposia report

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ANNALS OF THE NEW YORK ACADEMY OF SCIENCES 2023年第1期1523卷 38-50页

作者： Cable, Jennifer Rathmell, Jeffrey C. Pearce, Erika L. Ho, Ping-Chih Haigis, Marcia C. Mamedov, Murad R. Wu, Meng-Ju Kaech, Susan M. Lynch, Lydia Febbraio, Mark A. Bapat, Sagar P. Hong, Hanna S. Zou, Weiping Belkaid, Yasmine Sullivan, Zuri A. Keller, Andrea Wculek, Stefanie K. Green, Douglas R. Postic, Catherine Amit, Ido Benitah, Salvador Aznar Jones, Russell G. Reina-Campos, Miguel Torres, Santiago Valle Beyaz, Semir Brennan, Donal O'Neill, Luke A. J. Perry, Rachel J. Brenner, Dirk PhD Sci Writer New York NY 10017 USA Vanderbilt Univ Vanderbilt Ingram Canc Ctr Med Ctr Nashville TN USA Vanderbilt Univ Vanderbilt Ctr Immunobiol Med Ctr Nashville TN USA Vanderbilt Univ Dept Pathol Microbiol & Immunol Med Ctr Nashville TN USA Bloomberg Kimmel Inst Canc Immunotherapy Johns Ho Baltimore MD USA Max Planck Inst Immunobiol & Epigenet Freiburg Germany Univ Lausanne Dept Fundamental Oncol Lausanne Switzerland Univ Lausanne Ludwig Inst Canc Res Lausanne Switzerland Harvard Med Sch Blavatnik Inst Dept Cell Biol Boston MA USA Univ Calif San Francisco Gladstone UCSF Inst Genom Immunol San Francisco CA USA Univ Calif San Francisco Dept Med San Francisco CA USA Harvard Med Sch Massachusetts Gen Hosp Canc Ctr Boston MA USA Harvard Med Sch Dept Med Boston MA USA Broad Inst Harvard & MIT Cambridge MA USA Salk Inst Biol Studies NOMIS Ctr Immunobiol & Microbial Pathogenesis La Jolla CA USA Harvard Med Sch Brigham & Womens Hosp Boston MA USA Monash Univ Monash Inst Pharmaceut Sci Parkville VIC Australia Univ Calif San Francisco Diabet Ctr San Francisco CA USA Univ Calif San Francisco Dept Lab Med San Francisco CA USA Univ Michigan Dept Mol & Integrat Physiol Ann Arbor MI USA Univ Michigan Dept Surg Sch Med Ann Arbor MI USA Univ Michigan Univ Michigan Rogel Canc Ctr Ctr Excellence Canc Immunol & Immunotherapy Sch Med Ann Arbor MI USA Univ Michigan Dept Pathol Grad Program Immunol Sch Med Ann Arbor MI USA Univ Michigan Grad Program Canc Biol Sch Med Ann Arbor MI USA NIH Metaorganism Immun Sect Lab Immune Syst Biol Bethesda MD USA NIAID NIAID Microbiome Program NIH Bethesda MD USA Harvard Univ Dept Immunobiol Mol & Cellular Biol Cambridge MA USA Ohio State Univ Coll Med Dept Biol Chem & Pharmacol Columbus OH USA Ohio State Univ Arthur G James Canc Hosp Comprehens Canc Ctr Wexner Med Ctr Columbus OH USA Ctr Nacl Invest Cardiovasc CNIC Madrid Spain St Jude Childrens Res Hosp Memphis TN USA Univ Paris Cite Inst Coch

Immunometabolism considers the relationship between metabolism and immunity. Typically, researchers focus on either the metabolic pathways within immune cells that affect their function or the impact of immune cells on systemic metabolism. A more holistic approach that considers both these viewpoints is needed. On September 5-8, 2022, experts in the field of immunometabolism met for the Keystone symposium "Immunometabolism at the Crossroads of Obesity and Cancer" to present recent research across the field of immunometabolism, with the setting of obesity and cancer as an ideal example of the complex interplay between metabolism, immunity, and cancer. Speakers highlighted new insights on the metabolic links between tumor cells and immune cells, with a focus on leveraging unique metabolic vulnerabilities of different cell types in the tumor microenvironment as therapeutic targets and demonstrated the effects of diet, the microbiome, and obesity on immune system function and cancer pathogenesis and therapy. Finally, speakers presented new technologies to interrogate the immune system and uncover novel metabolic pathways important for immunity.

关键词： cancer immunity immunometabolism immunotherapy metabolism obesity

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Continuous Integration in Distributed Applied Software Packages 42

Continuous Integration in Distributed Applied Software Packa...

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42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)

作者： Feoktistov, A. G. Gorsky, S. A. Sidorov, I. A. Tchernykh, A. RAS SB Matrosov Inst Syst Dynam & Control Theory Irkutsk Russia CICESE Res Ctr Dept Comp Sci Ensenada Baja California Mexico RAS Ivannikov Inst Syst Programming Moscow Russia South Ural State Univ Chelyabinsk Russia

ISBN: (纸本)9789532330984

The paper addresses a new approach to supporting the continuous integration of modules for distributed applied software packages (scientific applications) that are developed in the Orlando Tools framework. We consider the packages for implementing experiments in heterogeneous distributed computing environments that integrate Grid systems, cloud platforms, and resources of public access supercomputer centers. Such packages are characterized by the modular structure, intense change of algorithmic knowledge implemented by modules, computations scalability, and execution in heterogeneous resources. In the packages, computational processes are represented by problem-solving schemes that closely correlate with the workflow concept. The essence and novelty of the proposed approach come from the merge of a methodology creating the packages with the modern practice of software development based on continuous integration. We automate and unify module assembly processes on both the dedicated servers and package developer machines through using the specialized virtual machines. In contrast to the well-known tools, we support the synthesis of the test problem-solving schemes in the automated mode. The practical applications of the developed prototype of the continuous integration system show the significant reducing the time of debugging, testing, and deploying the package modules.

关键词： heterogeneous environment scientific applications modular approach continuous integration subject knowledge

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Software library for path planning in complex construction environments 12th

Software library for path planning in complex construction e...

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12th European Conference on Product and Process Modelling (ECPPM)

作者： Kazakov, K. Morozov, S. Semenov, V. Zolotov, V. RAS Ivannikov Inst Syst Programming Moscow Russia

ISBN: (纸本)9780429506215;9781138584136

Recently spatial-temporal (4D) modeling is becoming increasingly important in the construction industry due to better planning of project works. One of the advantages not reachable through the usage of traditional methods is the detection of spatial-temporal conflicts in construction schedules. In the paper mathematical methods and software tools for the detection of a special type of conflicts-path conflicts are discussed. A software library for path planning in complex construction environments with non-trivial topology and dynamic behavior is presented. The main attention is paid to its general organization, functionality and object-oriented design. Computational experiments confirm the efficiency of the library and its advanced capabilities for spatial-temporal validation of construction schedules against path conflicts.

关键词： 4D modeling motion planning collision detection software engineering

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Metastatic breast cancer cells are metabolically reprogrammed to maintain redox homeostasis during metastasis

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REDOX BIOLOGY 2024年 75卷 103276页

作者： Biondini, Marco Lehuede, Camille Tabaries, Sebastien Annis, Matthew G. Pacis, Alain Ma, Eric H. Tam, Christine Hsu, Brian E. Audet-Delage, Yannick Abu-Thuraia, Afnan Girondel, Charlotte Sabourin, Valerie Totten, Stephanie P. Russo, Mariana de Sa Tavares Bridon, Gaelle Avizonis, Daina Guiot, Marie-Christine St-Pierre, Julie Ursini-Siegel, Josie Jones, Russell Siegel, Peter M. McGill Univ Goodman Canc Inst Montreal PQ H3A 1A3 Canada McGill Univ Dept Med Montreal PQ H3A 1A3 Canada McGill Univ Canadian Ctr Computat Genom Montreal PQ H3A 0G1 Canada Van Andel Inst Dept Metab & Nutr Programming Grand Rapids MI USA Univ Ottawa Dept Biochem Microbiol & Immunol Ottawa ON K1H 8M5 Canada Univ Ottawa Ottawa Inst Syst Biol Ottawa ON K1H 8M5 Canada Sir Mortimer B Davis Jewish Hosp Lady Davis Inst Med Res Segal Canc Ctr Quebec City PQ H3A 1A3 Canada McGill Univ Hlth Ctr Montreal Neurol Hosp Inst Dept Pathol Quebec City PQ H3A 1A3 Canada

Metabolic rewiring is essential for tumor growth and progression to metastatic disease, yet little is known regarding how cancer cells modify their acquired metabolic programs in response to different metastatic microenvironments. We have previously shown that liver-metastatic breast cancer cells adopt an intrinsic metabolic program characterized by increased HIF-1 alpha activity and dependence on glycolysis. Here, we confirm by in vivo stable isotope tracing analysis (SITA) that liver-metastatic breast cancer cells retain a glycolytic profile when grown as mammary tumors or liver metastases. However, hepatic metastases exhibit unique metabolic adaptations including elevated expression of genes involved in glutathione (GSH) biosynthesis and reactive oxygen species (ROS) detoxification when compared to mammary tumors. Accordingly, breast-cancer-liver-metastases exhibited enhanced de novo GSH synthesis. Confirming their increased capacity to mitigate ROS-mediated damage, liver metastases display reduced levels of 8-Oxo-2 '-deoxyguanosine. Depletion of the catalytic subunit of the rate-limiting enzyme in glutathione biosynthesis, glutamate-cysteine ligase (GCLC), strongly reduced the capacity of breast cancer cells to form liver metastases, supporting the importance of these distinct metabolic adaptations. Loss of GCLC also affected the early steps of the metastatic cascade, leading to decreased numbers of circulating tumor cells (CTCs) and impaired metastasis to the liver and the lungs. Altogether, our results indicate that GSH metabolism could be targeted to prevent the dissemination of breast cancer cells.

关键词： Glutathione Breast cancer Liver metastasis Oxidative stress Metabolism Glycolysis HIF-1 alpha GCLC

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Real-Time Gait Reconstruction For Virtual Reality Using a Single Sensor

Real-Time Gait Reconstruction For Virtual Reality Using a Si...

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19th IEEE International Symposium on Mixed and Augmented Reality (ISMAR)

作者： Feigl, Tobias Gruner, Lisa Mutschler, Christopher Roth, Daniel Fraunhofer Inst Integrated Circuits IIS Nurnberg Germany Tech Univ Munich TUM Munich Germany Friedrich Alexander Univ FAU Erlangen Nurnberg Programming Syst Grp Nurnberg Germany Ludwig Maximilians Univ LMU Dept Stat Munich Germany Tech Univ Munich TUM Chair Comp Aided Med Procedures & Augmented Real Munich Germany

ISBN: (纸本)9781728176758

Embodying users through avatars based on motion tracking and reconstruction is an ongoing challenge for VR application developers. High quality VR systems use full-body tracking or inverse kinematics to reconstruct the motion of the lower extremities and control the avatar animation. Mobile systems are limited to the motion sensing of head-mounted displays (HMDs) and typically cannot offer this. We propose an approach to reconstruct gait motions from a single head-mounted accelerometer. We train our models to map head motions to corresponding ground truth gait phases. To reconstruct leg motion, the models predict gait phases to trigger equivalent synthetic animations. We designed four models: a threshold-based, a correlation-based, a Support Vector Machine (SVM) -based and a bidirectional long-term short-term memory (BLSTM) -based model. Our experiments show that, while the BLSTM approach is the most accurate, only the correlation approach runs on a mobile VR system in real time with sufficient accuracy. Our user study with 21 test subjects examined the effects of our approach on simulator sickness and showed significantly less negative effects on disorientation.

关键词： Human-centered computing Interaction paradigms Virtual reality

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Method of Activity of Intelligent Agent for Semantic Analysis of Software Requirements 10

Method of Activity of Intelligent Agent for Semantic Analysi...

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10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing systems - Technology and Applications (IDAACS)

作者： Pavlova, Olga Hovorushchenko, Tetiana Boyarchuk, Artem Khmelnytsky Natl Univ Comp Engn & Syst Programming Dept KhNU Inst Str 11 UA-29016 Khmelnytsky Ukraine Natl Aerosp Univ Comp Syst Networks & Cybersecur Dept Kharkiv Aviat Inst Chkalov Str 17 UA-61070 Kharkiv Ukraine

ISBN: (纸本)9781728140681

The paper deals with the development of the method of activity and the realization of the intelligent agent (IA) for semantic analysis of the natural language software requirements. This IA performs the analysis of the requirements, determines the number and percentage of missing indicators for determining the metrics of complexity and quality of software, displays which indicators are missing for each metric, and also forms the real ontology of the domain "Software Engineering" (part "Quality and complexity of software. Metric analysis"). During an experiment, which is conducted with the help of the realized IA, the semantic analysis of requirements for the Internet of Things (IoT)-system was performed. Such analysis provides an increase of the volume and ensures of the sufficiency of metric information in the software requirements, which, in turn, provides an improvement in the quality of the software of IoT-system.

关键词： natural language software requirements semantic analysis intelligent agent (IA) ontology-based intelligent agent (OBIA) Internet of Things (IoT)-system

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Non-architectural improvements for ECG classification using deep neural network

Non-architectural improvements for ECG classification using ...

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Ivannikov Ispras Open Conference (ISPRAS)

作者： Andreev, Pavel Ananev, Vladislav Avetisyan, Aram Makarov, Vladimir Gliner, Vadim Schuster, Assaf Karpulevich, Evgeny Russian Acad Sci Ivannikov Inst Syst Programming Moscow Russia Novgorod State Univ Veliky Novgorod Russia Kurchatov Inst Natl Res Ctr Moscow Russia Moscow Inst Phys & Technol Genome Technol & Bioinfonnat Res Ctr Dolgoprudnyi Russia Technion IIT Comp Sci Dept Haifa Israel Skolkovo Inst Sci & Technol Moscow Russia Natl Res Univ Higher Sch Econ Moscow Russia Lomonosov Moscow State Univ Moscow Russia

ISBN: (纸本)9781665412919

Due to the latest advances in machine learning algorithms new deep learning-based approaches to the interpretation of 12-lead electrocardiograms have been developed, demonstrating the quality of diagnostics comparable to the expert one. In this paper, we propose several techniques increasing the quality of ECG classification by a deep neural network. The techniques include patient metadata incorporation, signal denoising and self-adaptive model training. The experimental validation of the approaches was carried out on a novel dataset containing 64198 standard ECG recordings obtained during routine medical practice. The conducted experiments demonstrated statistically significant quality growth compared to the baseline, supporting the further application of our findings.

关键词： ECG Classification Convolutional Neural Network Deep Learning Denoising Self-Adaptive Learning

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