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  1. AU="Tumanov A"
  2. AU="Hsu, Rafael M C S"
  3. AU=Perfect John R
  4. AU="Francini, Saverio"
  5. AU="Hurley, David"
  6. AU=Thomas L
  7. AU="French, M S"
  8. AU=Bonek Krzysztof
  9. AU="Noviello, Colleen M"
  10. AU="Jill A. Hollenbach"
  11. AU="Bansal, Ramesh C."
  12. AU="Huang, Xuhua"
  13. AU="Latorre, Víctor"
  14. AU="Simon J. Waddell"
  15. AU="Luo, Yueming"

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  1. Artikel ; Online: Modeling of aeroelastic composite plates vibrations based on asymptotic theory

    Dimitrienko Yu. / Gubareva E. / Tumanov A.

    E3S Web of Conferences, Vol 376, p

    2023  Band 01039

    Abstract: The paper is devoted to solving the problem of aeroelastic deformation of multilayer thin composite plates. A theory of aeroelastic deformations of composite plates based on the application of the asymptotic averaging method and piston theory for ... ...

    Abstract The paper is devoted to solving the problem of aeroelastic deformation of multilayer thin composite plates. A theory of aeroelastic deformations of composite plates based on the application of the asymptotic averaging method and piston theory for modeling pressure on the body surface is proposed. The averaged equations of aeroelastic vibrations of composite plates are derived. An example of a numerical solution of the problem of one-dimensional bending vibrations of a composite plate based on the developed theory is given.
    Schlagwörter multilayer composite ; aeroelastic deformations ; asymptotic averaging method ; numerical solution ; Environmental sciences ; GE1-350
    Sprache Englisch
    Erscheinungsdatum 2023-01-01T00:00:00Z
    Verlag EDP Sciences
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  2. Artikel ; Online: Rev Protein Diversity in HIV-1 Group M Clades.

    Lebedev, Aleksey / Kim, Kristina / Ozhmegova, Ekaterina / Antonova, Anastasiia / Kazennova, Elena / Tumanov, Aleksandr / Kuznetsova, Anna

    Viruses

    2024  Band 16, Heft 5

    Abstract: The HIV-1 Rev protein expressed in the early stage of virus replication is involved in the nuclear export of some forms of virus RNA. Naturally occurring polymorphisms in the Rev protein could influence its activity. The association between the genetic ... ...

    Abstract The HIV-1 Rev protein expressed in the early stage of virus replication is involved in the nuclear export of some forms of virus RNA. Naturally occurring polymorphisms in the Rev protein could influence its activity. The association between the genetic features of different virus variants and HIV infection pathogenesis has been discussed for many years. In this study, Rev diversity among HIV-1 group M clades was analyzed to note the signatures that could influence Rev activity and, subsequently, clinical characteristics. From the Los Alamos HIV Sequence Database, 4962 Rev sequences were downloaded and 26 clades in HIV-1 group M were analyzed for amino acid changes, conservation in consensus sequences, and the presence of clade-specific amino acid substitutions (CSSs) and the Wu-Kabat protein variability coefficient (WK). Subtypes G, CRF 02_AG, B, and A1 showed the largest amino acid changes and diversity. The mean conservation of the Rev protein was 80.8%. In consensus sequences, signatures that could influence Rev activity were detected. In 15 out of 26 consensus sequences, an insertion associated with the reduced export activity of the Rev protein, 95QSQGTET96, was identified. A total of 32 CSSs were found in 16 clades, wherein A6 had the 41Q substitution in the functionally significant region of Rev. The high values of WK coefficient in sites 51 and 82, located on the Rev interaction surface, indicate the susceptibility of these positions to evolutionary replacements. Thus, the noted signatures require further investigation.
    Mesh-Begriff(e) HIV-1/genetics ; HIV-1/classification ; rev Gene Products, Human Immunodeficiency Virus/genetics ; rev Gene Products, Human Immunodeficiency Virus/metabolism ; Humans ; HIV Infections/virology ; Genetic Variation ; Phylogeny ; Amino Acid Substitution ; Amino Acid Sequence ; Consensus Sequence
    Chemische Substanzen rev Gene Products, Human Immunodeficiency Virus ; rev protein, Human Immunodeficiency Virus-1
    Sprache Englisch
    Erscheinungsdatum 2024-05-10
    Erscheinungsland Switzerland
    Dokumenttyp Journal Article
    ZDB-ID 2516098-9
    ISSN 1999-4915 ; 1999-4915
    ISSN (online) 1999-4915
    ISSN 1999-4915
    DOI 10.3390/v16050759
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  3. Buch ; Online: SuperFed

    Khare, Alind / Agrawal, Animesh / Lee, Myungjin / Tumanov, Alexey

    Weight Shared Federated Learning

    2023  

    Abstract: Federated Learning (FL) is a well-established technique for privacy preserving distributed training. Much attention has been given to various aspects of FL training. A growing number of applications that consume FL-trained models, however, increasingly ... ...

    Abstract Federated Learning (FL) is a well-established technique for privacy preserving distributed training. Much attention has been given to various aspects of FL training. A growing number of applications that consume FL-trained models, however, increasingly operate under dynamically and unpredictably variable conditions, rendering a single model insufficient. We argue for training a global family of models cost efficiently in a federated fashion. Training them independently for different tradeoff points incurs $O(k)$ cost for any k architectures of interest, however. Straightforward applications of FL techniques to recent weight-shared training approaches is either infeasible or prohibitively expensive. We propose SuperFed - an architectural framework that incurs $O(1)$ cost to co-train a large family of models in a federated fashion by leveraging weight-shared learning. We achieve an order of magnitude cost savings on both communication and computation by proposing two novel training mechanisms: (a) distribution of weight-shared models to federated clients, (b) central aggregation of arbitrarily overlapping weight-shared model parameters. The combination of these mechanisms is shown to reach an order of magnitude (9.43x) reduction in computation and communication cost for training a $5*10^{18}$-sized family of models, compared to independently training as few as $k = 9$ DNNs without any accuracy loss.
    Schlagwörter Computer Science - Machine Learning ; Computer Science - Distributed ; Parallel ; and Cluster Computing
    Thema/Rubrik (Code) 006
    Erscheinungsdatum 2023-01-25
    Erscheinungsland us
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  4. Buch ; Online: Signed Binarization

    Kuhar, Sachit / Jain, Yash / Tumanov, Alexey

    Unlocking Efficiency Through Repetition-Sparsity Trade-Off

    2023  

    Abstract: Efficient inference of Deep Neural Networks (DNNs) on resource-constrained edge devices is essential. Quantization and sparsity are key algorithmic techniques that translate to repetition and sparsity within tensors at the hardware-software interface. ... ...

    Abstract Efficient inference of Deep Neural Networks (DNNs) on resource-constrained edge devices is essential. Quantization and sparsity are key algorithmic techniques that translate to repetition and sparsity within tensors at the hardware-software interface. This paper introduces the concept of repetition-sparsity trade-off that helps explain computational efficiency during inference. We propose Signed Binarization, a unified co-design framework that synergistically integrates hardware-software systems, quantization functions, and representation learning techniques to address this trade-off. Our results demonstrate that Signed Binarization is more accurate than binarization with the same number of non-zero weights. Detailed analysis indicates that signed binarization generates a smaller distribution of effectual (non-zero) parameters nested within a larger distribution of total parameters, both of the same type, for a DNN block. Finally, our approach achieves a 26% speedup on real hardware, doubles energy efficiency, and reduces density by 2.8x compared to binary methods for ResNet 18, presenting an alternative solution for deploying efficient models in resource-limited environments.
    Schlagwörter Computer Science - Machine Learning ; Computer Science - Artificial Intelligence ; Computer Science - Computer Vision and Pattern Recognition
    Thema/Rubrik (Code) 006
    Erscheinungsdatum 2023-12-03
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    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  5. Artikel ; Online: Improving Emergency Response Systems in the Oil and Gas Industry To Reduce Environmental Damage

    Kostyuk A / Tumanov A / Tumanov V / Zybina O

    E3S Web of Conferences, Vol 221, p

    2020  Band 01008

    Abstract: The article identifies the main problems of eliminating the reduction of environmental damage by improving the response systems to man-made accidents at hazardous production facilities of the oil and gas complex. Risk factors for ensuring safety at a ... ...

    Abstract The article identifies the main problems of eliminating the reduction of environmental damage by improving the response systems to man-made accidents at hazardous production facilities of the oil and gas complex. Risk factors for ensuring safety at a hazardous production facility in the oil and gas industry are identified, the most significant risk factor is identified by the method of hierarchical analysis, and the problem of the engineering and technical factor in the system “man technical environment industrial environment environment” is revealed. “The solution to the problem is indicated the use of a developed mobile emergency response system, which makes it possible to halve the response time to an emergency. The developed response system can be applied at any hazardous production facility in the oil and gas industry due to its flexibility.
    Schlagwörter risk ; environmental damage ; emergency response ; risk management ; risk factors ; mobile emergency response system ; Environmental sciences ; GE1-350
    Sprache Englisch
    Erscheinungsdatum 2020-01-01T00:00:00Z
    Verlag EDP Sciences
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  6. Buch ; Online: Mode I and Mode II stress intensity factors and dislocation density behaviour in strain gradient plasticity

    Shlyannikov, V. / Martínez-Pañeda, E. / Tumanov, A. / Khamidullin, R.

    2021  

    Abstract: In this study, we use the mechanism-based strain gradient plasticity theory to evaluate both crack tip dislocation density behaviour and the coupled effect of the material plastic properties and the intrinsic material length on non-linear amplitude ... ...

    Abstract In this study, we use the mechanism-based strain gradient plasticity theory to evaluate both crack tip dislocation density behaviour and the coupled effect of the material plastic properties and the intrinsic material length on non-linear amplitude factors. The two planar classical stress-strain states are examined, namely, plane strain and plane stress, both under pure mode I and pure mode II loading conditions. The constitutive relations are based on Taylor's dislocation model, which enables gaining insights into the role of the increased dislocation density associated with large gradients in plastic strain near cracks. The material model is implemented in a commercial finite element (FE) software package using a user subroutine, and the nonlinear stress intensity factors (SIF) are evaluated as a function of the intrinsic material length, characterising the scale at which gradient effects become significant. As a result of the FE calculations of dislocation density distributions, the effects of both the fracture mode and the stress-strain state are determined. In pure mode I, the geometrically necessary dislocation (GND) density is located symmetrically with respect to the blunted crack tip. On the contrary, under pure mode II, the GND density becomes concentrated in the blunted and sharp parts of the crack tip. In this case, fracture initiation is shown to be likely to occur near the blunted region of the crack tip, where both the stress triaxiality and the GND density are at their maximum. The relation between the equilibrium state of dislocation densities and the intrinsic material length as well as the plastic SIF as a function of the work hardening exponent is discussed.
    Schlagwörter Physics - Applied Physics ; Condensed Matter - Materials Science ; Computer Science - Computational Engineering ; Finance ; and Science
    Thema/Rubrik (Code) 669
    Erscheinungsdatum 2021-10-18
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    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  7. Artikel: Distinct roles for LTalpha3 and LTalpha1beta2 produced by B cells contribute to their multi-faceted impact on ileitis.

    Randolph, Gwendalyn / Erlich, Emma / Czepielewski, Rafael / Field, Rachael / Dunning, Taylor / Saleh, Leila / Hoofnagle, Mark / Tumanov, Alexei / Guilak, Farshid / Brestoff, Jonathan

    Research square

    2024  

    Abstract: B lymphocytes may facilitate chronic inflammation through antibody production or secretion of cytokines, including lymphotoxin (LT)- ... ...

    Abstract B lymphocytes may facilitate chronic inflammation through antibody production or secretion of cytokines, including lymphotoxin (LT)-a
    Sprache Englisch
    Erscheinungsdatum 2024-02-26
    Erscheinungsland United States
    Dokumenttyp Preprint
    DOI 10.21203/rs.3.rs-3962916/v1
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  8. Artikel ; Online: Prevalence of HIV drug resistance at antiretroviral treatment failure across regions of Russia.

    Ozhmegova, Ekaterina / Lebedev, Aleksey / Antonova, Anastasiia / Kuznetsova, Anna / Kazennova, Elena / Kim, Kristina / Tumanov, Aleksandr / Bobkova, Marina

    HIV medicine

    2024  

    Abstract: Background: This study aimed to investigate mutations associated with, the causes of, and the conditions that contribute to HIV drug resistance (DR). This research provides crucial insights into the mechanisms through which HIV evades antiretroviral ... ...

    Abstract Background: This study aimed to investigate mutations associated with, the causes of, and the conditions that contribute to HIV drug resistance (DR). This research provides crucial insights into the mechanisms through which HIV evades antiretroviral drugs and suggests strategies to counter this phenomenon. Our objective was to assess the prevalence and structure of DR in HIV-1 across various regions in Russia and identify the primary factors influencing the development of HIV DR.
    Methods: The study used nucleotide sequences from the HIV-1 pol gene obtained from 1369 patients with a history of therapy and virological failure between 2005 and 2019 to analyze the frequency and structure of DR and the factors associated with it.
    Results: The analysed HIV-1 genotypes included viruses resistant to nucleoside reverse transcriptase inhibitors (NRTIs; 11.8%), non-nucleoside reverse transcriptase inhibitors (NNRTIs; 6.4%), and NRTIs + NNRTIs (31.7%). The mutations M184V/I and G190A/S/E were the most prevalent, accounting for 54.5% and 26.6%, respectively. The dominance of multiple DR persisted throughout the entire observation period. The likelihood of encountering drug-resistant variants was increased among men, patients in the late stage of infection, and those with a viral load <30 000 RNA copies/mL. Injection drug use was not associated with DR.
    Conclusion: This study has yielded new insights into HIV DR in Russia, offering valuable information to identify clinical or programmatic events warranting closer attention and support.
    Sprache Englisch
    Erscheinungsdatum 2024-04-07
    Erscheinungsland England
    Dokumenttyp Journal Article
    ZDB-ID 2001932-4
    ISSN 1468-1293 ; 1464-2662
    ISSN (online) 1468-1293
    ISSN 1464-2662
    DOI 10.1111/hiv.13642
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  9. Artikel ; Online: Recombinant Forms of HIV-1 in the Last Decade of the Epidemic in the Russian Federation.

    Antonova, Anastasiia / Kazennova, Elena / Lebedev, Aleksey / Ozhmegova, Ekaterina / Kuznetsova, Anna / Tumanov, Aleksandr / Bobkova, Marina

    Viruses

    2023  Band 15, Heft 12

    Abstract: Currently, HIV-1 displays a substantial level of genetic diversity on a global scale, partly attributed to its recombinant variants. This study seeks to identify and analyze HIV-1 recombinants in Russia during the last decade of the epidemic. A ... ...

    Abstract Currently, HIV-1 displays a substantial level of genetic diversity on a global scale, partly attributed to its recombinant variants. This study seeks to identify and analyze HIV-1 recombinants in Russia during the last decade of the epidemic. A comprehensive examination was conducted, encompassing 3178 partial pol sequences. Subtyping was achieved through various programs including COMET, the Stanford Database, REGA, jpHMM, RIP, and RDP4 for recombination analysis. The study also involved phylogenetic analysis to trace the origins of the identified recombinants. Primary resistance (PrimDR) prevalence and Drug Resistance Mutations (DRMs) were assessed. The study uncovered an overall proportion of recombinants at 8.7%, with a statistically significant increase in their frequency observed over time (
    Mesh-Begriff(e) Humans ; HIV Infections/epidemiology ; HIV-1/genetics ; Phylogeny ; HIV Seropositivity ; Russia/epidemiology ; Genotype
    Sprache Englisch
    Erscheinungsdatum 2023-11-25
    Erscheinungsland Switzerland
    Dokumenttyp Journal Article
    ZDB-ID 2516098-9
    ISSN 1999-4915 ; 1999-4915
    ISSN (online) 1999-4915
    ISSN 1999-4915
    DOI 10.3390/v15122312
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  10. Buch ; Online: Signed Binary Weight Networks

    Kuhar, Sachit / Tumanov, Alexey / Hoffman, Judy

    2022  

    Abstract: Efficient inference of Deep Neural Networks (DNNs) is essential to making AI ubiquitous. Two important algorithmic techniques have shown promise for enabling efficient inference - sparsity and binarization. These techniques translate into weight sparsity ...

    Abstract Efficient inference of Deep Neural Networks (DNNs) is essential to making AI ubiquitous. Two important algorithmic techniques have shown promise for enabling efficient inference - sparsity and binarization. These techniques translate into weight sparsity and weight repetition at the hardware-software level enabling the deployment of DNNs with critically low power and latency requirements. We propose a new method called signed-binary networks to improve efficiency further (by exploiting both weight sparsity and weight repetition together) while maintaining similar accuracy. Our method achieves comparable accuracy on ImageNet and CIFAR10 datasets with binary and can lead to 69% sparsity. We observe real speedup when deploying these models on general-purpose devices and show that this high percentage of unstructured sparsity can lead to a further reduction in energy consumption on ASICs.

    Comment: it is being updated
    Schlagwörter Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Distributed ; Parallel ; and Cluster Computing ; Computer Science - Performance
    Thema/Rubrik (Code) 006
    Erscheinungsdatum 2022-11-24
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    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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