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Article ; Online: Quantum hydrodynamic theory of quantum fluctuations in dipolar Bose-Einstein condensate.

Andreev, Pavel A

2021 Volume 31, Issue 2, Page(s) 23120

Abstract: Traditional quantum hydrodynamics of Bose-Einstein condensates (BECs) is restricted by the continuity and Euler equations. The quantum Bohm potential (the quantum part of the momentum flux) has a nontrivial part that can evolve under quantum fluctuations. ...

Abstract	Traditional quantum hydrodynamics of Bose-Einstein condensates (BECs) is restricted by the continuity and Euler equations. The quantum Bohm potential (the quantum part of the momentum flux) has a nontrivial part that can evolve under quantum fluctuations. The quantum fluctuations are the effect of the appearance of particles in the excited states during the evolution of BEC mainly consisting of the particles in the quantum state with the lowest energy. To cover this phenomenon in terms of hydrodynamic methods, we need to derive equations for the momentum flux and the current of the momentum flux. The current of the momentum flux evolution equation contains the interaction leading to the quantum fluctuations. In the dipolar BECs, we deal with the long-range interaction. Its contribution is proportional to the average macroscopic potential of the dipole-dipole interaction (DDI) appearing in the mean-field regime. The current of the momentum flux evolution equation contains the third derivative of this potential. It is responsible for the dipolar part of quantum fluctuations. Higher derivatives correspond to the small scale contributions of the DDI. The quantum fluctuations lead to the existence of the second wave solution. The quantum fluctuations introduce the instability of the BECs. If the dipole-dipole interaction is attractive, but being smaller than the repulsive short-range interaction presented by the first interaction constant, there is the long-wavelength instability. There is a more complex picture for the repulsive DDI. There is the small area with the long-wavelength instability that transits into a stability interval where two waves exist.
Language	English
Publishing date	2021-03-02
Publishing country	United States
Document type	Journal Article
ZDB-ID	1472677-4
ISSN	1089-7682 ; 1054-1500
ISSN (online)	1089-7682
ISSN	1054-1500
DOI	10.1063/5.0036511
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Article ; Online: The state of lead scoring models and their impact on sales performance.

Wu, Migao / Andreev, Pavel / Benyoucef, Morad

Information technology & management

2023 , Page(s) 1–30

Abstract: Although lead scoring is an essential component of lead management, there is a lack of a comprehensive literature review and a classification framework dedicated to it. Lead scoring is an effective and efficient way of measuring the quality of leads. In ... ...

Abstract	Although lead scoring is an essential component of lead management, there is a lack of a comprehensive literature review and a classification framework dedicated to it. Lead scoring is an effective and efficient way of measuring the quality of leads. In addition, as a critical Information Technology tool, a proper lead scoring model acts as an alleviator to weaken the conflicts between sales and marketing functions. Yet, little is known regarding lead scoring models and their impact on sales performance. Lead scoring models are commonly categorized into two classes: traditional and predictive. While the former primarily relies on the experience and knowledge of salespeople and marketers, the latter utilizes data mining models and machine learning algorithms to support the scoring process. This study aims to review and analyze the existing literature on lead scoring models and their impact on sales performance. A systematic literature review was conducted to examine lead scoring models. A total of 44 studies have met the criteria and were included for analysis. Fourteen metrics were identified to measure the impact of lead scoring models on sales performance. With the increased use of data mining and machine learning techniques in the fourth industrial revolution, predictive lead scoring models are expected to replace traditional lead scoring models as they positively impact sales performance. Despite the relative cost of implementing and maintaining predictive lead scoring models, it is still beneficial to supersede traditional lead scoring models, given the higher effectiveness and efficiency of predictive lead scoring models. This study reveals that classification is the most popular data mining model, while decision tree and logistic regression are the most applied algorithms among all the predictive lead scoring models. This study contributes by systematizing and recommending which machine learning method (i.e., supervised and/or unsupervised) shall be used to build predictive lead scoring models based on the integrity of different types of data sources. Additionally, this study offers both theoretical and practical research directions in the lead scoring field.
Language	English
Publishing date	2023-02-01
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2035174-4
ISSN	1573-7667 ; 1385-951X
ISSN (online)	1573-7667
ISSN	1385-951X
DOI	10.1007/s10799-023-00388-w
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Book ; Online: A new microscopic representation of the spin dynamics in quantum systems with the Coulomb exchange interactions

Trukhanova, Mariya Iv. / Andreev, Pavel

2023

Abstract: There is a version of the Landau-Lifshitz equation that takes into account the Coulomb exchange interactions between atoms, expressed by the term $\sim\bm{s}\times\triangle\bm{s}$. On the other hand, ions in the magnetic materials have several valence ... ...

Abstract	There is a version of the Landau-Lifshitz equation that takes into account the Coulomb exchange interactions between atoms, expressed by the term $\sim\bm{s}\times\triangle\bm{s}$. On the other hand, ions in the magnetic materials have several valence electrons on the $d$-shell, and therefore the Hamiltonian of many-electron atoms with spins $S>1$ should include a biquadratic exchange interaction. We first propose a new fundamental microscopic derivation of the spin density evolution equation with an explicit form of biquadratic exchange interaction using the method of many-particle quantum hydrodynamics. The equation for the evolution of the spin density is obtained from the many-particle Schrodinger-Pauli equation and contains the contributions of the usual Coulomb exchange interaction and the biquadratic exchange. Furthermore, the derived biquadratic exchange torque in the spin density evolution equation is proportional to the nematic tensor for the medium of atoms with spin $\textit{S = 1}$. Our method may be very attractive for further studies of the magnetoelectric effect in multiferroics.
Keywords	Condensed Matter - Materials Science
Subject code	530
Publishing date	2023-05-05
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: A new quantum hydrodynamic description of ferroelectricity in spiral magnets

Trukhanova, Mariya Iv. / Andreev, Pavel A. / Obukhov, Yuri N.

2023

Abstract: The strong coupling between magnetism and ferroelectricity was found in rare earth manganites, where the electric polarization could be induced by special magnetic ordering. There is no theoretical model that would allow us to study the static and ... ...

Abstract	The strong coupling between magnetism and ferroelectricity was found in rare earth manganites, where the electric polarization could be induced by special magnetic ordering. There is no theoretical model that would allow us to study the static and dynamic properties of electric polarization in strongly correlated magnetic dielectrics. In the presented research, we have taken the main step towards the construction of such a fundamental model. A novel description of the ferroelectricity of spin origin is proposed within the framework of the many-particle quantum hydrodynamics method. It is applied to the study of clusters of magnetic ions, where the electric dipole moment can be induced as a result of spin-orbit coupling and is proportional to the vector product of spins. Our approach is based on the many-particle Pauli equation, where the influence of an external magnetic field is considered. We define the electric dipole moment operator of the ion cluster and introduce the macroscopic polarization as the quantum mechanical average of that operator. We formulate a model for the description of nonequilibrium polarization and derive a new polarization evolution equation. The polarization switching in ferroelectric magnets with the spiral spin-density-wave state is considered, and we demonstrate that the proposed model yields known results and predicts novel effects. The dynamic magnetoelectric effect can be investigated by employing this novel equation to study the evolution of polarization.
Keywords	Condensed Matter - Materials Science ; Condensed Matter - Strongly Correlated Electrons
Subject code	530
Publishing date	2023-11-06
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Separated spin-up and spin-down quantum hydrodynamics of degenerated electrons: Spin-electron acoustic wave appearance.

Andreev, Pavel A

Physical review. E, Statistical, nonlinear, and soft matter physics

2015 Volume 91, Issue 3, Page(s) 33111

Abstract: The quantum hydrodynamic (QHD) model of charged spin-1/2 particles contains physical quantities defined for all particles of a species including particles with spin-up and with spin-down. Different populations of states with different spin directions are ...

Abstract	The quantum hydrodynamic (QHD) model of charged spin-1/2 particles contains physical quantities defined for all particles of a species including particles with spin-up and with spin-down. Different populations of states with different spin directions are included in the spin density (the magnetization). In this paper I derive a QHD model, which separately describes spin-up electrons and spin-down electrons. Hence electrons with different projections of spins on the preferable direction are considered as two different species of particles. It is shown that the numbers of particles with different spin directions do not conserve. Hence the continuity equations contain sources of particles. These sources are caused by the interactions of the spins with the magnetic field. Terms of similar nature arise in the Euler equation. The z projection of the spin density is no longer an independent variable. It is proportional to the difference between the concentrations of the electrons with spin-up and the electrons with spin-down. The propagation of waves in the magnetized plasmas of degenerate electrons is considered. Two regimes for the ion dynamics, the motionless ions and the motion of the degenerate ions as the single species with no account of the spin dynamics, are considered. It is shown that this form of the QHD equations gives all solutions obtained from the traditional form of QHD equations with no distinction of spin-up and spin-down states. But it also reveals a soundlike solution called the spin-electron acoustic wave. Coincidence of most solutions is expected since this derivation was started with the same basic equation: the Pauli equation. Solutions arise due to the different Fermi pressures for the spin-up electrons and the spin-down electrons in the magnetic field. The results are applied to degenerate electron gas of paramagnetic and ferromagnetic metals in the external magnetic field. The dispersion of the spin-electron acoustic waves in the partially spin-polarized degenerate neutron matter are also considered.
Language	English
Publishing date	2015-03
Publishing country	United States
Document type	Journal Article
ISSN	1550-2376
ISSN (online)	1550-2376
DOI	10.1103/PhysRevE.91.033111
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Book ; Online: UnDiff

Iashchenko, Anastasiia / Andreev, Pavel / Shchekotov, Ivan / Babaev, Nicholas / Vetrov, Dmitry

Unsupervised Voice Restoration with Unconditional Diffusion Model

2023

Abstract: This paper introduces UnDiff, a diffusion probabilistic model capable of solving various speech inverse tasks. Being once trained for speech waveform generation in an unconditional manner, it can be adapted to different tasks including degradation ... ...

Abstract	This paper introduces UnDiff, a diffusion probabilistic model capable of solving various speech inverse tasks. Being once trained for speech waveform generation in an unconditional manner, it can be adapted to different tasks including degradation inversion, neural vocoding, and source separation. In this paper, we, first, tackle the challenging problem of unconditional waveform generation by comparing different neural architectures and preconditioning domains. After that, we demonstrate how the trained unconditional diffusion could be adapted to different tasks of speech processing by the means of recent developments in post-training conditioning of diffusion models. Finally, we demonstrate the performance of the proposed technique on the tasks of bandwidth extension, declipping, vocoding, and speech source separation and compare it to the baselines. The codes are publicly available. Comment: Accepted to Interspeech 2023
Keywords	Computer Science - Sound ; Computer Science - Artificial Intelligence ; Electrical Engineering and Systems Science - Audio and Speech Processing
Subject code	410
Publishing date	2023-06-01
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: HiFi++

Andreev, Pavel / Alanov, Aibek / Ivanov, Oleg / Vetrov, Dmitry

a Unified Framework for Bandwidth Extension and Speech Enhancement

2022

Abstract: Generative adversarial networks have recently demonstrated outstanding performance in neural vocoding outperforming best autoregressive and flow-based models. In this paper, we show that this success can be extended to other tasks of conditional audio ... ...

Abstract	Generative adversarial networks have recently demonstrated outstanding performance in neural vocoding outperforming best autoregressive and flow-based models. In this paper, we show that this success can be extended to other tasks of conditional audio generation. In particular, building upon HiFi vocoders, we propose a novel HiFi++ general framework for bandwidth extension and speech enhancement. We show that with the improved generator architecture, HiFi++ performs better or comparably with the state-of-the-art in these tasks while spending significantly less computational resources. The effectiveness of our approach is validated through a series of extensive experiments. Comment: Accepted to ICASSP 2023
Keywords	Computer Science - Sound ; Computer Science - Machine Learning ; Electrical Engineering and Systems Science - Audio and Speech Processing
Publishing date	2022-03-24
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: MHealth and perceived quality of care delivery: a conceptual model and validation.

O'Connor, Yvonne / Andreev, Pavel / O'Reilly, Philip

BMC medical informatics and decision making

2020 Volume 20, Issue 1, Page(s) 41

Abstract: Background: The objective of this research is to examine, conceptualize, and empirically validate a model of mobile health (mHealth) impacts on physicians' perceived quality of care delivery (PQoC).: Methods: Observational quasi-experimental one ... ...

Abstract	Background: The objective of this research is to examine, conceptualize, and empirically validate a model of mobile health (mHealth) impacts on physicians' perceived quality of care delivery (PQoC). Methods: Observational quasi-experimental one group posttest-only design was implemented through the empirical testing of the conceptual model with nine hypotheses related to the association of task and technology characteristics, self-efficacy, m-health utilization, task-technology fit (TTF), and their relationships with PQoC. Primary data was collected over a four-month period from acute care physicians in The Ottawa Hospital, Ontario, Canada. The self-reported data was collected by employing a survey and distributed through the internal hospital channels to physicians who adopted iPads for their daily activities. Results: Physicians' PQoC was found to be positively affected by the level of mHealth utilization and TTF, while the magnitude of the TTF direct effect was two times stronger than utilization. Additionally, self-efficacy has the highest direct and total effect on mHealth utilization; in the formation of TTF, technological characteristics dominate followed by task characteristics. Conclusion: To date, the impact of utilized mHealth on PQoC has neither been richly theorized nor explored in depth. We address this gap in existing literature. Realizing how an organization can improve TTF will lead to better PQoC.
MeSH term(s)	Adolescent ; Adult ; Aged ; Female ; Humans ; Latent Class Analysis ; Male ; Middle Aged ; Models, Theoretical ; Ontario ; Physicians/psychology ; Quality of Health Care ; Reproducibility of Results ; Self Efficacy ; Self Report ; Task Performance and Analysis ; Telemedicine/statistics & numerical data
Language	English
Publishing date	2020-02-27
Publishing country	England
Document type	Journal Article ; Observational Study
ISSN	1472-6947
ISSN (online)	1472-6947
DOI	10.1186/s12911-020-1049-8
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Book ; Online: Quantization of Generative Adversarial Networks for Efficient Inference

Andreev, Pavel / Fritzler, Alexander / Vetrov, Dmitry

a Methodological Study

2021

Abstract: Generative adversarial networks (GANs) have an enormous potential impact on digital content creation, e.g., photo-realistic digital avatars, semantic content editing, and quality enhancement of speech and images. However, the performance of modern GANs ... ...

Abstract	Generative adversarial networks (GANs) have an enormous potential impact on digital content creation, e.g., photo-realistic digital avatars, semantic content editing, and quality enhancement of speech and images. However, the performance of modern GANs comes together with massive amounts of computations performed during the inference and high energy consumption. That complicates, or even makes impossible, their deployment on edge devices. The problem can be reduced with quantization -- a neural network compression technique that facilitates hardware-friendly inference by replacing floating-point computations with low-bit integer ones. While quantization is well established for discriminative models, the performance of modern quantization techniques in application to GANs remains unclear. GANs generate content of a more complex structure than discriminative models, and thus quantization of GANs is significantly more challenging. To tackle this problem, we perform an extensive experimental study of state-of-art quantization techniques on three diverse GAN architectures, namely StyleGAN, Self-Attention GAN, and CycleGAN. As a result, we discovered practical recipes that allowed us to successfully quantize these models for inference with 4/8-bit weights and 8-bit activations while preserving the quality of the original full-precision models.
Keywords	Computer Science - Artificial Intelligence ; Computer Science - Machine Learning
Subject code	006
Publishing date	2021-08-31
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: FFC-SE

Shchekotov, Ivan / Andreev, Pavel / Ivanov, Oleg / Alanov, Aibek / Vetrov, Dmitry

Fast Fourier Convolution for Speech Enhancement

2022

Abstract: Fast Fourier convolution (FFC) is the recently proposed neural operator showing promising performance in several computer vision problems. The FFC operator allows employing large receptive field operations within early layers of the neural network. It ... ...

Abstract	Fast Fourier convolution (FFC) is the recently proposed neural operator showing promising performance in several computer vision problems. The FFC operator allows employing large receptive field operations within early layers of the neural network. It was shown to be especially helpful for inpainting of periodic structures which are common in audio processing. In this work, we design neural network architectures which adapt FFC for speech enhancement. We hypothesize that a large receptive field allows these networks to produce more coherent phases than vanilla convolutional models, and validate this hypothesis experimentally. We found that neural networks based on Fast Fourier convolution outperform analogous convolutional models and show better or comparable results with other speech enhancement baselines. Comment: Submitted to INTERSPEECH 2022
Keywords	Computer Science - Sound ; Computer Science - Artificial Intelligence ; Electrical Engineering and Systems Science - Audio and Speech Processing
Subject code	006
Publishing date	2022-04-06
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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