Article
Computer Science, Theory & Methods
Zongmin Ma, Li Yan
Summary: This paper provides a comprehensive survey on the current state of the art in fuzzy data modeling and querying. It focuses on three crucial issues in fuzzy techniques for data management: modeling fuzzy data, querying fuzzy data, and fuzzy queries over crisp data. The paper identifies different fuzzy data models and summarizes their query processing. It also reviews fuzzy querying over classical data models.
FUZZY SETS AND SYSTEMS
(2022)
Article
Engineering, Environmental
Tomasz Ujazdowski, Tomasz Zubowicz, Robert Piotrowski
Summary: The aim of this research is to provide a comprehensive description of modeling the Sequencing Batch Reactor (SBR) for monitoring, control, and plant operational optimization validation. The paper presents a detailed modeling of the SBR and its components, using the mass balance principle and continuity equations implemented with the Activated Sludge Model (ASM). Spatially discretized models along the vertical axis are used in numerical experiments. The simulations enable comparison of different models of activated sludge settling velocity and approaches to modeling reactions in the SBR.
JOURNAL OF WATER PROCESS ENGINEERING
(2023)
Article
Multidisciplinary Sciences
Yolanda Escobar, Cesar Margarit, Concepcion Perez-Hernandez, Teresa Quintanar, Juan A. Virizuela
Summary: The treatment of oncological pain requires a multidisciplinary management approach between oncology services and pain units. However, many patients do not receive appropriate referral and management. This survey aimed to identify barriers and propose recommendations to improve the management of cancer pain by emphasizing collaboration and coordination between oncology services and pain units.
SCIENTIFIC REPORTS
(2022)
Article
Chemistry, Physical
Dong Chen, Jiaxin Zheng, Guo-Wei Wei, Feng Pan
Summary: The study introduces a self-supervised learning approach to pretrain models from unlabeled molecules and extract predictive representations for specific tasks. Extensive validation indicates that the proposed method shows superb performance.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2021)
Article
Biochemical Research Methods
Ngoc-Quang Nguyen, Gwanghoon Jang, Hajung Kim, Jaewoo Kang
Summary: Compound-protein interaction (CPI) is crucial in drug discovery, and there have been AI-based approaches proposed to study it. Two types of models, graph convolutional neural networks and neural networks applied to molecular descriptors or fingerprints, have shown promising results. However, it is still unclear which method is superior. This study presents the Perceiver CPI network, which utilizes a cross-attention mechanism and rich information from extended-connectivity fingerprints to enhance the learning ability and performance. The proposed method outperforms previous approaches in all experiments on three main datasets.
Article
Mathematics
Qingsong Mao, Huan Huang
Summary: This paper introduced the interval range of fuzzy sets and the arithmetic operations defined based on it, discussing the importance of interval range and its impact on arithmetic operations. By presenting general conclusions, it indicated the need to modify previous research conclusions and the relationship between the interval ranges of fuzzy sets and compositions of finite arithmetic.
Article
Chemistry, Medicinal
Jiarui Chen, Hong Hin Cheong, Shirley W. Siu
Summary: This study used deep learning to predict the biological activity of anticancer peptides against six tumor cells, showing that multitask learning models performed better than single-task models. The best models achieved low mean squared error and high correlation coefficients in cross validation. By inferring the contribution of residues to activity, the interpretability of the model's predictions was enhanced.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2021)
Article
Chemistry, Medicinal
Xujun Zhang, Chao Shen, Ben Liao, Dejun Jiang, Jike Wang, Zhenxing Wu, Hongyan Du, Tianyue Wang, Wenbo Huo, Lei Xu, Dongsheng Cao, Chang-Yu Hsieh, Tingjun Hou
Summary: The development of accurate machine-learning-based scoring functions for virtual screening requires unbiased and diverse datasets. However, most existing datasets may suffer from hidden biases and data insufficiency. In this study, we developed a new approach named TocoDecoy to generate unbiased and expandable datasets, and evaluated its performance compared to other datasets.
JOURNAL OF MEDICINAL CHEMISTRY
(2022)
Article
Multidisciplinary Sciences
Marius Arend, David Zimmer, Rudan Xu, Frederik Sommer, Timo Muehlhaus, Zoran Nikoloski
Summary: Metabolic engineering of microalgae can be improved by integrating enzyme turnover numbers and quantitative protein abundance data, which provides valuable information on enzyme catalytic rates and improves predictions on enzyme usage and allocation.
NATURE COMMUNICATIONS
(2023)
Article
Biochemical Research Methods
Thomas Sauter, Tamara Bintener, Ali Kishk, Luana Presta, Tessy Prohaska, Daniel Guignard, Ni Zeng, Claudia Cipriani, Sundas Arshad, Thomas Pfau, Patricia Martins Conde, Maria Pires Pacheco
Summary: This article introduces a long-standing project-based learning course within the Master in Integrated Systems Biology program at the University of Luxembourg, which aims to cultivate students' ability to solve real-life problems and promote engagement and critical thinking. The article provides a detailed description of the course schedule and content, showcases student projects, and reflects on the outcomes and lessons learned.
PLOS COMPUTATIONAL BIOLOGY
(2022)
Article
Obstetrics & Gynecology
Martine De Rycke, Antonio Capalbo, Edith Coonen, Giovanni Coticchio, Francesco Fiorentino, Veerle Goossens, Saria Mcheik, Carmen Rubio, Karen Sermon, Ioannis Sfontouris, Claudia Spits, Joris Robert Vermeesch, Nathalie Vermeulen, Dagan Wells, Filippo Zambelli, Georgia Kakourou
Summary: This study provides 30 good practice recommendations for ART/PGT centres to manage the detection of chromosomal mosaicism in 'mosaic' embryos. Data shows varying criteria for designating mosaicism, reporting and transfer policies across centres, emphasizing the need for standardized practices.
HUMAN REPRODUCTION OPEN
(2022)
Article
Food Science & Technology
Soren Saxmose Nielsen, Julio Alvarez, Paolo Calistri, Elisabetta Canali, Julian Ashley Drewe, Bruno Garin-Bastuji, Jose Luis Gonzales Rojas, Christian Gortazar, Mette Herskin, Virginie Michel, Miguel Angel Miranda Chueca, Barbara Padalino, Paolo Pasquali, Helen Clare Roberts, Hans Spoolder, Karl Stahl, Antonio Velarde, Arvo Viltrop, Christoph Winckler, Andrea Gervelmeyer, Yves Van Der Stede, Dominique Joseph Bicout
Summary: The EFSA requested the development of a guidance document on using models for scientific assessments in animal health. This document provides a detailed operating procedure to transparently and consistently integrate modelling in the assessment process.
Article
Chemistry, Medicinal
Andrew T. McNutt, Fatimah Bisiriyu, Sophia Song, Ananya Vyas, Geoffrey R. Hutchison, David Ryan Koes
Summary: This study empirically elucidates the general principles of the size, diversity, and quality of conformational ensembles needed for optimal performance in structure-based drug discovery tasks. It compares the performance of state-of-the-art generative deep learning approach with a classical geometry-based approach and investigates the effects of energy minimization, ensemble size, construction, and their impact on recapitulating bioactive conformations and performing pharmacophore screening and molecular docking.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Computer Science, Artificial Intelligence
Anton Batliner, Simone Hantke, Bjorn Schuller
Summary: With the rapid development of artificial intelligence, ethical considerations have gained increasing attention. However, there is still insufficient focus on ethical issues in the field of computational paralinguistics. This article provides an overview of ethics and privacy, describes the field of computational paralinguistics and its applications, and proposes guidelines for good practice, establishing a foundation for ethical standards in the field.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Faruk Karaaslan, Naim Cagman
Summary: Soft set theory is an important tool for dealing with uncertainty. In this study, parameter trees are introduced using mappings from parameter set into power set of parameter set. Operations between parameter trees are defined and their properties are obtained. A similarity measure method between parameter trees is also provided.
Review
Water Resources
Kelly Hill, Arash Zamyadi, Dan Deere, Peter A. Vanrolleghem, Nicholas D. Crosbie
Summary: Wastewater surveillance of pathogens is a useful tool to assess the effectiveness of disease monitoring, providing a sensitive and rapid indicator of infection rate changes. Models can be used to back-calculate wastewater prevalence to population prevalence, as well as help design wastewater sampling strategies.
WATER QUALITY RESEARCH JOURNAL
(2021)
Article
Engineering, Chemical
Majid Gholami Shirkoohi, Rajeshwar D. Tyagi, Peter A. Vanrolleghem, Patrick Drogui
Summary: This study evaluates the effectiveness of a modelling and optimization methodology based on artificial neural networks and genetic algorithms in predicting the behavior of an electrolysis process. Trained ANN models successfully predicted the active chlorine production and energy consumption, leading to insights on optimal operating conditions. Multi-objective optimization using genetic algorithms resulted in non-dominated optimal points for maximizing active chlorine production and minimizing energy consumption.
CANADIAN JOURNAL OF CHEMICAL ENGINEERING
(2021)
Article
Agricultural Engineering
Zhipeng Zhang, Qian Ping, Dan Gao, Peter A. Vanrolleghem, Yongmei Li
Summary: This study investigates the effects of different forms of Fe(III)Ps on phosphorus release and the performance of waste activated sludge (WAS) during anaerobic fermentation. The results show that Fe(III)Ps have diverse impacts on P release and the efficiency of anaerobic fermentation, with certain Fe(III)Ps even inhibiting the fermentation process.
BIORESOURCE TECHNOLOGY
(2021)
Editorial Material
Engineering, Environmental
James C. Young, Peter A. Vanrolleghem
Summary: The standard 5-day biochemical oxygen demand (BOD5) measurement is widely used in designing water resource recovery facilities, but the component of nitrogenous oxygen demand (NOD) should be taken into consideration to avoid oversizing. Carbonaceous BOD (CBOD5) is more accurate for sizing aerobic treatment processes based on the biodegradation of organic constituents in wastewater. Nitrogenous oxygen demand is important for nitrogen removal processes.
WATER ENVIRONMENT RESEARCH
(2021)
Article
Environmental Sciences
Benedicte Bakan, Nicolas Bernet, Theodore Bouchez, Rachel Boutrou, Jean-Marc Choubert, Patrick Dabert, Christian Duquennoi, Vincenza Ferraro, Diana Garcia-Bernet, Sylvie Gillot, Jacques Mery, Caroline Remond, Jean-Philippe Steyer, Eric Trably, Anne Tremier
Summary: The article discusses the importance of turning organic residues and wastewater into valuable assets and presents key directions and challenges for driving the development of circular bioeconomy solutions. By proposing innovative processes, establishing multi-scale cross-sectoral organizations, and enhancing research-legislation interactions, the resourceful utilization of organic residues and wastewater can be achieved.
WASTE AND BIOMASS VALORIZATION
(2022)
Article
Engineering, Chemical
Timo Larsson, Camilo Duran Quintero, Sylvie Gillot, Arnaud Cockx, Yannick Fayolle
Summary: This study aimed to develop a model coupling hydrodynamics and mass transfer to understand measurements on air-water bubble columns with low gas hold-up. The model analyzed the significant impact of local hydrostatic pressure and contamination on hydrodynamic and mass transfer parameters, showing that oxygen concentration in gas decreases significantly with distance from diffusers. The impact of water quality on mass transfer can be characterized by the contamination angle, highlighting a differentiated impact on hydrodynamic or mass transfer parameters.
CHEMICAL ENGINEERING SCIENCE
(2022)
Article
Engineering, Environmental
Feiyi Li, Peter A. Vanrolleghem
Summary: Modeling, automation, and control are widely used in the upgrading and optimization of Water Resource Recovery Facilities (WRRF). The current calibration of the influent generator (IG) models needs to consider the temporal variability of the dataset and optimize it using a multi-objective genetic algorithm. The developed model can generate a probability distribution time series that better represents reality, providing a better description for the design and operation of WRRF.
WATER SCIENCE AND TECHNOLOGY
(2022)
Article
Engineering, Chemical
Majid Gholami Shirkoohi, Rajeshwar D. Tyagi, Peter A. Vanrolleghem, Patrick Drogui
Summary: This study investigated the modelling and optimization of electrochemical oxidation (EO) process for the removal of psychoactive pharmaceutical caffeine in synthetic solution and real municipal wastewater effluent. The central composite design (CCD) based on response surface methodology (RSM) and adaptive neuro fuzzy inference system (ANFIS) were used to analyze the influence of independent variables on caffeine degradation. Both CCD and ANFIS models successfully predicted the electrochemical process behavior, with the ANFIS models performing slightly better. The degradation of caffeine by the EO process followed an oxidation pathway similar to other advanced oxidation processes. The optimal conditions determined using CCD were applied to real municipal wastewater effluent, demonstrating the effectiveness of the process. However, the EO process may increase the toxicity levels of the wastewater effluent, which can be reduced by extending the electrolysis time or using granular activated carbon.
SEPARATION AND PURIFICATION TECHNOLOGY
(2022)
Article
Engineering, Environmental
Elena Torfs, Niels Nicolai, Saba Daneshgar, John B. Copp, Henri Haimi, David Ikumi, Bruce Johnson, Benedek B. Plosz, Spencer Snowling, Lloyd R. Townley, Borja Valverde-Perez, Peter A. Vanrolleghem, Luca Vezzaro, Ingmar Nopens
Summary: Digital Twins (DTs) are innovative and powerful technologies that utilize digitalization in the WRRF sector. However, the lack of consensus and understanding regarding the definition, perceived benefits, and technological needs of DTs hinders their widespread development and application in this field. This paper provides an overview of the state-of-the-art, challenges, good practices, development needs, and transformative capacity of DTs for WRRF applications.
WATER SCIENCE AND TECHNOLOGY
(2022)
Article
Engineering, Environmental
Gamze Kirim, Kester McCullough, Thiago Bressani Ribeiro, Carlos Domingo-Felez, Haoran Duan, Ahmed Al-Omari, Haydee De Clippeleir, Jose Jimenez, Stephanie Klaus, Mojolaoluwa Ladipo-Obasa, Javad Mehrani, Pusker Regmi, Elena Torfs, Eveline I. P. Volcke, Peter A. Vanrolleghem
Summary: This article provides an overview of the current state-of-the-art in modelling short-cut nitrogen removal processes in mainstream wastewater treatment, identifying future research directions and challenges. The importance of mathematical models in considering N2O emissions and the need for new, advanced approaches are emphasized.
WATER SCIENCE AND TECHNOLOGY
(2022)
Article
Engineering, Environmental
Feiyi Li, Peter A. Vanrolleghem
Summary: A new data-driven influent generator (IG) model is proposed in this study, which only uses routine data and weather information without the need for additional data collection. The model can generate reliable flowrate and quality data at different time scales and resolutions.
WATER SCIENCE AND TECHNOLOGY
(2022)
Review
Engineering, Environmental
Majid Gholami Shirkoohi, Rajeshwar Dayal Tyagi, Peter A. Vanrolleghem, Patrick Drogui
Summary: This paper reviews the application of artificial intelligence techniques in water and wastewater treatment processes, specifically focusing on electrochemical processes. The study highlights the importance of reliability and robustness of the AI models developed using techniques such as artificial neural networks and support vector machines.
JOURNAL OF ENVIRONMENTAL HEALTH SCIENCE AND ENGINEERING
(2022)
Article
Environmental Sciences
Raheleh Arabgol, Peter A. Vanrolleghem, Robert Delatolla
Summary: This study evaluates the influence of carrier geometric properties and biofilm thickness levels on the characteristics and settleability of solids in the moving bed biofilm reactor (MBBR) system. The ViCAs method is used to assess particle settling velocities in the MBBR effluent, combined with microscopy imaging to relate particle size distribution to settling velocity. The results show that the commonly used AnoxK TM K5 carrier demonstrates different biofilm characteristics and settling behavior compared to the newly designed thickness-restraint carriers (AnoxK TM Z-carriers). Furthermore, statistical analysis confirms that different carrier types and biofilm thickness levels have significant effects on biofilm characteristics and particle settling properties in the MBBR system.
JOURNAL OF ENVIRONMENTAL SCIENCES
(2022)
Article
Engineering, Environmental
Mostafa Khalil, Ahmed Alsayed, Yang Liu, Peter A. Vanrolleghem
Summary: This study develops a comprehensive approach for using machine learning to perform online process modeling of N2O emissions, providing operators with the insights needed for informed corrective actions. By employing feature selection and parametric multivariate outlier removal methods, the complexity and data collection cost of modeling are reduced without significant effect on accuracy. The highest performing models are kNN, AdaBoost, and DNN.
Article
Engineering, Environmental
Feiyi Li, Peter A. Vanrolleghem
Summary: A data-driven methodology is proposed in this study to create an influent generator (IG) model that accurately describes the influent flow and water temperature dynamics under the impact of snowmelt in cold climate conditions. The performance of the model is evaluated and compared with a phenomenological model, showing that the proposed model has better accuracy.
ENVIRONMENTAL SCIENCE-WATER RESEARCH & TECHNOLOGY
(2022)
