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Article ; Online: Investigation of Dipolar Response of the Hydrated Hen-Egg White Lysozyme Complex under Externally Applied Electric Fields: Insights from Non-equilibrium Molecular Dynamics.

Wu, HaoLun / Ghaani, Mohammad Reza / Nandi, Prithwish K / English, Niall J

The journal of physical chemistry. B

2022 Volume 126, Issue 4, Page(s) 858–868

Abstract: Given its ubiquitous presence in the environment of bio-macromolecules, water is well known to play a fundamental part in biological activity, often as a regulating agent. In parallel, with increasing attention focused on the potential damage of ... ...

Abstract	Given its ubiquitous presence in the environment of bio-macromolecules, water is well known to play a fundamental part in biological activity, often as a regulating agent. In parallel, with increasing attention focused on the potential damage of microwave-frequency radiation exposure to human health, the effects of extraneous electric and electromagnetic (e/m) fields on water shells surrounding proteins, and, indeed, biomolecules themselves, are becoming a particularly pertinent issue. In this study, non-equilibrium molecular dynamics simulations of hydrated hen-egg white lysozyme have been performed in both the absence and presence of external electric fields of varying intensity (0.005-0.02 V/Å) and frequency (static,
MeSH term(s)	Animals ; Chickens ; Egg White ; Electricity ; Female ; Humans ; Molecular Dynamics Simulation ; Muramidase/chemistry ; Water/chemistry
Chemical Substances	Water (059QF0KO0R) ; Muramidase (EC 3.2.1.17)
Language	English
Publishing date	2022-01-21
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1520-5207
ISSN (online)	1520-5207
DOI	10.1021/acs.jpcb.1c07096
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Effects of Externally Applied Electric Fields on the Manipulation of Solvated-Chignolin Folding: Static- versus Alternating-Field Dichotomy at Play.

Wu, HaoLun / Ghaani, Mohammad Reza / Futera, Zdeněk / English, Niall J

The journal of physical chemistry. B

2022 Volume 126, Issue 2, Page(s) 376–386

Abstract: The interaction between a protein and external electric field (EF) can alter its structure and dynamical behavior, which has a potential impact on the biological function of proteins and cause uncertain health consequences. Conversely, the application of ...

Abstract	The interaction between a protein and external electric field (EF) can alter its structure and dynamical behavior, which has a potential impact on the biological function of proteins and cause uncertain health consequences. Conversely, the application of EFs of judiciously selected intensity and frequency can help to treat disease, and optimization of this requires a greater understanding of EF-induced effects underpinning basic protein biophysics. In the present study, chignolin─an artificial protein sufficiently small to undergo fast-folding events and transitions─was selected as an ideal prototype to investigate how, and to what extent, externally applied electric fields may manipulate or influence protein-folding phenomena. Nonequilibrium molecular dynamics (NEMD) simulations have been performed of solvated chignolin to determine the distribution of folding states and their underlying transition dynamics, in the absence and presence of externally applied electric fields (both static and alternating); a key focus has been to ascertain how folding pathways are altered in an athermal sense by external fields. Compared to zero-field conditions, a dramatically different─indeed, bifurcated─behavior of chignolin-folding processes emerges between static- and alternating-field scenarios, especially vis-à-vis incipient stages of hydrophobic-core formation: in alternating fields, fold-state populations diversified, with an attendant acceleration of state-hopping folding kinetics, featuring the concomitant emergence of a new, quasi-stable structure compared to the native structure, in field-shifted energy landscapes.
MeSH term(s)	Electricity ; Molecular Dynamics Simulation ; Oligopeptides/chemistry ; Protein Folding
Chemical Substances	Oligopeptides ; chignolin
Language	English
Publishing date	2022-01-10
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1520-5207
ISSN (online)	1520-5207
DOI	10.1021/acs.jpcb.1c06857
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Article: Effects of Externally Applied Electric Fields on the Manipulation of Solvated-Chignolin Folding: Static- versus Alternating-Field Dichotomy at Play

Wu, HaoLun / Ghaani, Mohammad Reza / Futera, Zdeněk / English, Niall J.

Journal of physical chemistry. 2022 Jan. 10, v. 126, no. 2

2022

Abstract	The interaction between a protein and external electric field (EF) can alter its structure and dynamical behavior, which has a potential impact on the biological function of proteins and cause uncertain health consequences. Conversely, the application of EFs of judiciously selected intensity and frequency can help to treat disease, and optimization of this requires a greater understanding of EF-induced effects underpinning basic protein biophysics. In the present study, chignolin─an artificial protein sufficiently small to undergo fast-folding events and transitions─was selected as an ideal prototype to investigate how, and to what extent, externally applied electric fields may manipulate or influence protein-folding phenomena. Nonequilibrium molecular dynamics (NEMD) simulations have been performed of solvated chignolin to determine the distribution of folding states and their underlying transition dynamics, in the absence and presence of externally applied electric fields (both static and alternating); a key focus has been to ascertain how folding pathways are altered in an athermal sense by external fields. Compared to zero-field conditions, a dramatically different─indeed, bifurcated─behavior of chignolin-folding processes emerges between static- and alternating-field scenarios, especially vis-à-vis incipient stages of hydrophobic-core formation: in alternating fields, fold-state populations diversified, with an attendant acceleration of state-hopping folding kinetics, featuring the concomitant emergence of a new, quasi-stable structure compared to the native structure, in field-shifted energy landscapes.
Keywords	biophysics ; electric field ; molecular dynamics ; protein folding ; prototypes
Language	English
Dates of publication	2022-0110
Size	p. 376-386.
Publishing place	American Chemical Society
Document type	Article
ISSN	1520-5207
DOI	10.1021/acs.jpcb.1c06857
Database	NAL-Catalogue (AGRICOLA)

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Article: Investigation of Dipolar Response of the Hydrated Hen-Egg White Lysozyme Complex under Externally Applied Electric Fields: Insights from Non-equilibrium Molecular Dynamics

Wu, HaoLun / Ghaani, Mohammad Reza / Nandi, Prithwish K. / English, Niall J.

Journal of physical chemistry. 2022 Jan. 21, v. 126, no. 4

2022

Abstract	Given its ubiquitous presence in the environment of bio-macromolecules, water is well known to play a fundamental part in biological activity, often as a regulating agent. In parallel, with increasing attention focused on the potential damage of microwave-frequency radiation exposure to human health, the effects of extraneous electric and electromagnetic (e/m) fields on water shells surrounding proteins, and, indeed, biomolecules themselves, are becoming a particularly pertinent issue. In this study, non-equilibrium molecular dynamics simulations of hydrated hen-egg white lysozyme have been performed in both the absence and presence of external electric fields of varying intensity (0.005–0.02 V/Å) and frequency (static, i.e., zero-frequency, together with oscillating fields of 2.45–100 GHz). By comparing the effect of different electric-field conditions on both the protein’s and surrounding hydration layer’s dipole moments and their underlying relaxation dynamics, clear and evident non-thermal field effects were observed on the dipolar response of both the protein and hydration layer. This occurred primarily as a consequence of the protein’s dipolar alignment with the external field and increased with the growth of field intensity. In addition, it was found that the lag time of dipolar response to the applied field itself, for both the protein and the first hydration sub-shell (i.e., directly adsorbed layer), under oscillating fields is longer than that in both the second hydration sub-layer and bulk water, owing to strong direct protein–water adsorption. In that respect, we also probe and discuss the effect of protein–water hydrogen bonds, dissecting the subtleties of “bio-water” dipolar response.
Keywords	adsorption ; bioactive properties ; electric field ; human health ; hydrogen ; lysozyme ; molecular dynamics
Language	English
Dates of publication	2022-0121
Size	p. 858-868.
Publishing place	American Chemical Society
Document type	Article
ISSN	1520-5207
DOI	10.1021/acs.jpcb.1c07096
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Thickness-dependent carrier transport of PdSe

Zhang, Rui / Zhang, Qiusong / Jia, Xinyu / Wen, Shaofeng / Wu, Haolun / Gong, Yimin / Yin, Yi / Lan, Changyong / Li, Chun

Nanotechnology

2023 Volume 34, Issue 34

Abstract: Atomically thin narrow-bandgap layered ... ...

Abstract	Atomically thin narrow-bandgap layered PdSe
Language	English
Publishing date	2023-06-12
Publishing country	England
Document type	Journal Article
ZDB-ID	1362365-5
ISSN	1361-6528 ; 0957-4484
ISSN (online)	1361-6528
ISSN	0957-4484
DOI	10.1088/1361-6528/acd855
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Book ; Online: Joint Multisided Exposure Fairness for Recommendation

Wu, Haolun / Mitra, Bhaskar / Ma, Chen / Diaz, Fernando / Liu, Xue

2022

Abstract: Prior research on exposure fairness in the context of recommender systems has focused mostly on disparities in the exposure of individual or groups of items to individual users of the system. The problem of how individual or groups of items may be ... ...

Abstract	Prior research on exposure fairness in the context of recommender systems has focused mostly on disparities in the exposure of individual or groups of items to individual users of the system. The problem of how individual or groups of items may be systemically under or over exposed to groups of users, or even all users, has received relatively less attention. However, such systemic disparities in information exposure can result in observable social harms, such as withholding economic opportunities from historically marginalized groups (allocative harm) or amplifying gendered and racialized stereotypes (representational harm). Previously, Diaz et al. developed the expected exposure metric -- that incorporates existing user browsing models that have previously been developed for information retrieval -- to study fairness of content exposure to individual users. We extend their proposed framework to formalize a family of exposure fairness metrics that model the problem jointly from the perspective of both the consumers and producers. Specifically, we consider group attributes for both types of stakeholders to identify and mitigate fairness concerns that go beyond individual users and items towards more systemic biases in recommendation. Furthermore, we study and discuss the relationships between the different exposure fairness dimensions proposed in this paper, as well as demonstrate how stochastic ranking policies can be optimized towards said fairness goals.
Keywords	Computer Science - Information Retrieval ; Computer Science - Artificial Intelligence ; Computer Science - Machine Learning
Publishing date	2022-04-29
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Feature Representation Learning for Click-through Rate Prediction

Lyu, Fuyuan / Tang, Xing / Liu, Dugang / Wu, Haolun / Ma, Chen / He, Xiuqiang / Liu, Xue

A Review and New Perspectives

2023

Abstract: Representation learning has been a critical topic in machine learning. In Click-through Rate Prediction, most features are represented as embedding vectors and learned simultaneously with other parameters in the model. With the development of CTR models, ...

Abstract	Representation learning has been a critical topic in machine learning. In Click-through Rate Prediction, most features are represented as embedding vectors and learned simultaneously with other parameters in the model. With the development of CTR models, feature representation learning has become a trending topic and has been extensively studied by both industrial and academic researchers in recent years. This survey aims at summarizing the feature representation learning in a broader picture and pave the way for future research. To achieve such a goal, we first present a taxonomy of current research methods on feature representation learning following two main issues: (i) which feature to represent and (ii) how to represent these features. Then we give a detailed description of each method regarding these two issues. Finally, the review concludes with a discussion on the future directions of this field. Comment: Submitted to IJCAI 2023 Survey Track
Keywords	Computer Science - Information Retrieval
Subject code	004
Publishing date	2023-02-04
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Density-based User Representation through Gaussian Process Regression for Multi-interest Personalized Retrieval

Wu, Haolun / Meshi, Ofer / Zoghi, Masrour / Diaz, Fernando / Liu, Xue / Boutilier, Craig / Karimzadehgan, Maryam

2023

Abstract: Accurate modeling of the diverse and dynamic interests of users remains a significant challenge in the design of personalized recommender systems. Existing user modeling methods, like single-point and multi-point representations, have limitations w.r.t. ... ...

Abstract	Accurate modeling of the diverse and dynamic interests of users remains a significant challenge in the design of personalized recommender systems. Existing user modeling methods, like single-point and multi-point representations, have limitations w.r.t. accuracy, diversity, computational cost, and adaptability. To overcome these deficiencies, we introduce density-based user representations (DURs), a novel model that leverages Gaussian process regression for effective multi-interest recommendation and retrieval. Our approach, GPR4DUR, exploits DURs to capture user interest variability without manual tuning, incorporates uncertainty-awareness, and scales well to large numbers of users. Experiments using real-world offline datasets confirm the adaptability and efficiency of GPR4DUR, while online experiments with simulated users demonstrate its ability to address the exploration-exploitation trade-off by effectively utilizing model uncertainty. Comment: 16 pages, 5 figures
Keywords	Computer Science - Information Retrieval
Subject code	004
Publishing date	2023-10-30
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Multi-FR

Wu, Haolun / Ma, Chen / Mitra, Bhaskar / Diaz, Fernando / Liu, Xue

A Multi-objective Optimization Framework for Multi-stakeholder Fairness-aware Recommendation

2021

Abstract: Nowadays, most online services are hosted on multi-stakeholder marketplaces, where consumers and producers may have different objectives. Conventional recommendation systems, however, mainly focus on maximizing consumers' satisfaction by recommending the ...

Abstract	Nowadays, most online services are hosted on multi-stakeholder marketplaces, where consumers and producers may have different objectives. Conventional recommendation systems, however, mainly focus on maximizing consumers' satisfaction by recommending the most relevant items to each individual. This may result in unfair exposure of items, thus jeopardizing producer benefits. Additionally, they do not care whether consumers from diverse demographic groups are equally satisfied. To address these limitations, we propose a multi-objective optimization framework for fairness-aware recommendation, Multi-FR, that adaptively balances accuracy and fairness for various stakeholders with Pareto optimality guarantee. We first propose four fairness constraints on consumers and producers. In order to train the whole framework in an end-to-end way, we utilize the smooth rank and stochastic ranking policy to make these fairness criteria differentiable and friendly to back-propagation. Then, we adopt the multiple gradient descent algorithm to generate a Pareto set of solutions, from which the most appropriate one is selected by the Least Misery Strategy. The experimental results demonstrate that Multi-FR largely improves recommendation fairness on multiple stakeholders over the state-of-the-art approaches while maintaining almost the same recommendation accuracy. The training efficiency study confirms our model's ability to simultaneously optimize different fairness constraints for many stakeholders efficiently. Comment: 29 pages
Keywords	Computer Science - Information Retrieval
Subject code	004
Publishing date	2021-05-06
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Adapting Triplet Importance of Implicit Feedback for Personalized Recommendation

Wu, Haolun / Ma, Chen / Zhang, Yingxue / Liu, Xue / Tang, Ruiming / Coates, Mark

2022

Abstract: Implicit feedback is frequently used for developing personalized recommendation services due to its ubiquity and accessibility in real-world systems. In order to effectively utilize such information, most research adopts the pairwise ranking method on ... ...

Abstract	Implicit feedback is frequently used for developing personalized recommendation services due to its ubiquity and accessibility in real-world systems. In order to effectively utilize such information, most research adopts the pairwise ranking method on constructed training triplets (user, positive item, negative item) and aims to distinguish between positive items and negative items for each user. However, most of these methods treat all the training triplets equally, which ignores the subtle difference between different positive or negative items. On the other hand, even though some other works make use of the auxiliary information (e.g., dwell time) of user behaviors to capture this subtle difference, such auxiliary information is hard to obtain. To mitigate the aforementioned problems, we propose a novel training framework named Triplet Importance Learning (TIL), which adaptively learns the importance score of training triplets. We devise two strategies for the importance score generation and formulate the whole procedure as a bilevel optimization, which does not require any rule-based design. We integrate the proposed training procedure with several Matrix Factorization (MF)- and Graph Neural Network (GNN)-based recommendation models, demonstrating the compatibility of our framework. Via a comparison using three real-world datasets with many state-of-the-art methods, we show that our proposed method outperforms the best existing models by 3-21\% in terms of Recall@k for the top-k recommendation.
Keywords	Computer Science - Information Retrieval ; Computer Science - Machine Learning
Subject code	006
Publishing date	2022-08-02
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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