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14th International Conference on Practical Applications of Computational Biology and Bioinformatics, PACBB 2020

作者： Pérez-Pérez, Martín Lourenço, Anália Igrejas, Gilberto Fdez-Riverola, Florentino ESEI Department of Computer Science University of Vigo Edificio Politécnico Campus Universitario as Lagoas s/n 32004 Ourense Spain CINBIO The Biomedical Research Centre University of Vigo Campus Univesitario Lagoas-Marcosende Vigo36310 Spain SING Next Generation Computer Systems Group Galicia Sur Health Research Institute SERGAS-UVIGO Vigo Spain CEB Centre of Biological Engineering University of Minho Campus de Gualtar Braga4710-057 Portugal Department of Genetics and Biotechnology University of Trás-os-Montes and Alto Douro Vila Real Portugal Functional Genomics and Proteomics Unit University of Trás-os-Montes and Alto Douro Vila Real Portugal LAQV-REQUIMTE Faculty of Science and Technology Nova University of Lisbon Lisbon Portugal

ISBN: (纸本)9783030545673

Concerning the field of Health sciences, one of the trends with the greatest impact today is related to the feeding and consumption of foods intended for chronic patients with a nutritional association. According to this, the gluten-free diet is one of the diets with a today’s fastest-growing due to their health therapy associations for different diseases and because of more and more people are freely choosing to follow a gluten-free diet. On this subject, e-commerce platforms are destined to be a key point for the sale of this kind of products due to: (i) the change in the business model caused by the electronic platforms and (ii) the expected increase consumption of disease designed special foods. For this reason, the experiences written by chronic disease patients and consumers in these platforms have become increasingly relevant. In this sense, the present work applies biomedical text mining methods and demographic knowledge inference techniques to a large number of gluten-free foods consumer’s experiences to discover a wide range of health-related topics associated to gluten-free products, alimentary social trends and demographics differences. The results of these analyses show significant trends over time;differences between males and females consumption and a wide range of health-related conclusions, such as: why consumers start a free gluten diet or what are the most discussed diseases and adverse reactions related to these products. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Nutrition

A Normal Distribution Transform-Based Radar Odometry Designed For Scanning and Automotive Radars

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arXiv 2021年

作者： Kung, Pou-Chun Wang, Chieh-Chih Lin, Wen-Chieh Graduate Degree Program of Robotics National Chiao Tung University Hsinchu Taiwan Department of Electrical and Computer Engineering National Chiao Tung University The Mechanical and Mechatronics Systems Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan Department of Computer Science National Chiao Tung University Hsinchu Taiwan

Existing radar sensors can be classified into automotive and scanning radars. While most radar odometry (RO) methods are only designed for a specific type of radar, our RO method adapts to both scanning and automotive radars. Our RO is simple yet effective, where the pipeline consists of thresholding, probabilistic submap building, and an NDT-based radar scan matching. The proposed RO has been tested on two public radar datasets: the Oxford Radar RobotCar dataset and the nuScenes dataset, which provide scanning and automotive radar data respectively. The results show that our approach surpasses state-of-the-art RO using either automotive or scanning radar by reducing translational error by 51% and 30%, respectively, and rotational error by 17% and 29%, respectively. Besides, we show that our RO achieves centimeter-level accuracy as lidar odometry, and automotive and scanning RO have similar accuracy. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical radar

Biomimetic robots promote the 3Rs Principle in animal testing

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Biomimetic robots promote the 3Rs Principle in animal testin...

2021 Conference on Artificial Life, ALIFE 2021

作者： Bierbach, David Francisco, Fritz Lukas, Juliane Landgraf, Tim Maxeiner, Moritz Romanczuk, Pawel Musiolek, Lea Hafner, Verena V. Krause, Jens Faculty of Life Sciences Division of Biology and Ecology of Fishes Humboldt Universität zu Berlin Berlin Germany Department of Biology and Ecology of Fishes Leibniz Institute of Freshwater Ecology and Inland Fisheries Berlin Germany Dahlem Center for Machine Learning and Robotics Freie Universität Berlin Berlin Germany Faculty of Life Sciences Institute for Theoretical Biology Humboldt Universität zu Berlin Berlin Germany Adaptive Systems Group Department of Computer Science Humboldt-Universität zu Berlin Berlin Germany

In order to strengthen animal welfare, many countries require that experimenters follow the ‘3Rs Principle’ when designing animal experiments. The 3Rs call for a reduction in the number of animals used, the refinement of methods to reduce stress as well as the full replacement of animals in experimentation through alternative methods. Biomimetic robots that resemble live animals and allow for natural-like interactions represent a valuable tool to achieve the 3Rs’ objectives. On the basis of our research with a robotic fish that is accepted as a conspecific by live poeciliid fishes, we highlight how biomimetic robots can reduce the number of animals tested by (a) substituting live animals, (b) providing highly standardized cues, and (c) reducing overall stress for live animals during tests through less handling. © 2021 ALIFE. All Rights Reserved.

关键词： Invertebrates

Temporal memory relation network for workflow recognition from surgical video

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arXiv 2021年

作者： Jin, Yueming Long, Yonghao Chen, Cheng Zhao, Zixu Dou, Qi Heng, Pheng-Ann Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong Department of Computer Science and Engineering T Stone Robotics Institute Chinese University of Hong Kong Hong Kong Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China

Automatic surgical workflow recognition is a key component for developing context-aware computer-assisted systems in the operating theatre. Previous works either jointly modeled the spatial features with short fixed-range temporal information, or separately learned visual and long temporal cues. In this paper, we propose a novel end-to-end temporal memory relation network (TMRNet) for relating long-range and multi-scale temporal patterns to augment the present features. We establish a long-range memory bank to serve as a memory cell storing the rich supportive information. Through our designed temporal variation layer, the supportive cues are further enhanced by multi-scale temporal-only convolutions. To effectively incorporate the two types of cues without disturbing the joint learning of spatio-temporal features, we introduce a non-local bank operator to attentively relate the past to the present. In this regard, our TMRNet enables the current feature to view the long-range temporal dependency, as well as tolerate complex temporal extents. We have extensively validated our approach on two benchmark surgical video datasets, M2CAI challenge dataset and Cholec80 dataset. Experimental results demonstrate the outstanding performance of our method, consistently exceeding the state-of-the-art methods by a large margin (e.g., 67.0% v.s. 78.9% Jaccard on Cholec80 dataset). Copyright © 2021, The Authors. All rights reserved.

关键词： Surgery

COSMIC: fast closed-form identification from large-scale data for LTV systems

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arXiv 2021年

作者： Carvalho, Maria Soares, Claudia Lourenco, Pedro Ventura, Rodrigo GMV Portugal Instituto Superior Técnico U. de Lisboa Portugal NOVA LINCS Computer Science Department Nova School of Science and Technology U. Nova de Lisboa Portugal Institute for Systems and Robotics Lisboa Portugal

We introduce a closed-form method for identification of discrete-time linear time-variant systems from data, formulating the learning problem as a regularized least squares problem where the regularizer favors smooth solutions within a trajectory. We develop a closed-form algorithm with guarantees of optimality and with a complexity that increases linearly with the number of instants considered per trajectory. The COSMIC algorithm achieves the desired result even in the presence of large volumes of data. Our method solved the problem using two orders of magnitude less computational power than a general purpose convex solver and was about 3 times faster than a Stochastic Block Coordinate Descent especially designed method. Computational times of our method remained in the order of magnitude of the second even for 10k and 100k time instants, where the general purpose solver crashed. To prove its applicability to real world systems, we test with spring-mass-damper system and use the estimated model to find the optimal control path. Our algorithm was applied to both a Low Fidelity and Functional Engineering Simulators for the Comet Interceptor mission, that requires precise pointing of the on-board cameras in a fast dynamics environment. Thus, this paper provides a fast alternative to classical system identification techniques for linear time-variant systems, while proving to be a solid base for applications in the Space industry and a step forward to the incorporation of algorithms that leverage data in such a safety-critical environment. © 2021, CC BY.

关键词： Accident prevention

Simultaneously Calibration of Multi Hand-Eye Robot System Based on Graph

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arXiv 2023年

作者： Zhou, Zishun Ma, Liping Liu, Xilong Cao, Zhiqiang Yu, Junzhi The Institute of Automation Chinese Academy of Sciences Beijing100190 China The College of Electrical Engineering and Computer Science Australian National University Canberra2601 Australia The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China The State Key Laboratory for Turbulence and Complex System Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Peking University Beijing100871 China

Precise calibration is the basis for the vision-guided robot system to achieve high-precision operations. systems with multiple eyes (cameras) and multiple hands (robots) are particularly sensitive to calibration errors, such as micro-assembly systems. Most existing methods focus on the calibration of a single unit of the whole system, such as poses between hand and eye, or between two hands. These methods can be used to determine the relative pose between each unit, but the serialized incremental calibration strategy cannot avoid the problem of error accumulation in a large-scale system. Instead of focusing on a single unit, this paper models the multi-eye and multi-hand system calibration problem as a graph and proposes a method based on the minimum spanning tree and graph optimization. This method can automatically plan the serialized optimal calibration strategy in accordance with the system settings to get coarse calibration results initially. Then, with these initial values, the closed-loop constraints are introduced to carry out global optimization. Simulation experiments demonstrate the performance of the proposed algorithm under different noises and various hand-eye configurations. In addition, experiments on real robot systems are presented to further verify the proposed method. © 2023, CC BY-SA.

关键词： Multipurpose robots

Robust and Precise Facial Landmark Detection by Self-Calibrated Pose Attention Network

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arXiv 2021年

作者： Wan, Jun Xi, Hui Zhou, Jie Lai, Zhihui Pedrycz, Witold Wang, Xu Sun, Hang School of Information and Safety Engineering Zhongnan University of Economics and Law Wuhan430073 China College of Computer Science and Software Engineering Shen zhen University Shenzhen518060 China Computer Vision Institute College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China Department of Electrical & Computer Engineering University of Alberta Edmonton Canada Systems Research Institute Polish Academy of Sciences Warsaw Poland College of Computer and Information Technology China Three Gorges University Yichang HuBei China

Current fully-supervised facial landmark detection methods have progressed rapidly and achieved remarkable performance. However, they still suffer when coping with faces under large poses and heavy occlusions for inaccurate facial shape constraints and insufficient labeled training samples. In this paper, we propose a semi-supervised framework, i.e., a Self-Calibrated Pose Attention Network (SCPAN) to achieve more robust and precise facial landmark detection in challenging scenarios. To be specific, a Boundary-Aware Landmark Intensity (BALI) field is proposed to model more effective facial shape constraints by fusing boundary and landmark intensity field information. Moreover, a Self-Calibrated Pose Attention (SCPA) model is designed to provide a self-learned objective function that enforces intermediate supervision without label information by introducing a self-calibrated mechanism and a pose attention mask. We show that by integrating the BALI fields and SCPA model into a novel self-calibrated pose attention network, more facial prior knowledge can be learned and the detection accuracy and robustness of our method for faces with large poses and heavy occlusions have been improved. The experimental results obtained for challenging benchmark datasets demonstrate that our approach outperforms state-of-the-art methods in the literature. Copyright © 2021, The Authors. All rights reserved.

关键词： Face recognition

Modeling of adsorptive removal of azithromycin from aquatic media by CoFe₂O₄_/NiO anchored microalgae-derived nitrogen-doped porous activated carbon adsorbent and colorimetric quantifying of azithromycin in pharmaceutical products

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Chemosphere 2023年第1期329卷 138635页

作者： Ameen, Fuad Mostafazadeh, Reza Hamidian, Yasamin Erk, Nevin Sanati, Afsaneh L. Karaman, Ceren Ayati, Ali Department of Botany and Microbiology College of Science King Saud University Riyadh 11451 Saudi Arabia Ankara University Faculty of Pharmacy Department of Analytical Chemistry Ankara 06560 Turkey Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Polo II Coimbra 3030-290 Portugal Akdeniz University Vocational School of Technical Sciences Department of Electricity and Energy Antalya 07070 Turkey ChemBio Cluster ITMO University Lomonosova Street 9 Saint Petersburg 191002 Russian Federation

Herein, it was aimed to optimize the removal process of Azithromycin (Azi) from the aquatic environment via CoFe2O4/NiO nanoparticles anchored onto the microalgae-derived nitrogen-doped porous activated carbon (N-PAC)... 详细信息

Herein, it was aimed to optimize the removal process of Azithromycin (Azi) from the aquatic environment via CoFe₂O₄_/NiO nanoparticles anchored onto the microalgae-derived nitrogen-doped porous activated carbon (N-PAC), besides developing a colorimetric method for the swift monitoring of Azi in pharmaceutical products. In this study, the Spirulina platensis (Sp) was used as a biomass resource for fabricating CoFe₂O₄/NiO@N-PAC adsorbent. The pores of N-PAC mainly entail mesoporous structures with a mean pore diameter of 21.546 nm and total cavity volume (V_total) of 0.033578 cm³. g⁻¹. The adsorption studies offered that 98.5% of Azi in aqueous media could remove by CoFe₂O₄/NiO@N-PAC. For the cyclic stability analysis, the adsorbent was separated magnetically and assessed at the end of five adsorption-desorption cycles with a negligible decrease in adsorption. The kinetic modeling revealed that the adsorption of Azi onto the CoFe₂O₄/NiO@N-PAC was well-fitted to the second-order reaction kinetics, and the highest adsorption capacity was found as 2000 mg. g⁻¹ at 25 °C based on the Langmuir adsorption isotherm model at 0.8 g. L⁻¹ adsorbent concentration. The Freundlich isotherm model had the best agreement with the experimental data. Thermodynamic modeling indicated the spontaneous and exothermic nature of the adsorption process. Moreover, the effects of pH, temperature, and operating time were also optimized in the colorimetric Azi detection. The blue ion-pair complexes between Azi and Coomassie Brilliant Blue G-250 (CBBG-250) reagent followed Beer's law at wavelengths of 640 nm in the concentration range of 1.0 μM to 1.0 mM with a 0.94 μM limit of detection (LOD). In addition, the selectivity of Azi determination was verified in presence of various species. Furthermore, the applicability of CBBG-250 dye for quantifying

关键词： Adsorption Adsorption modeling Azithromycin Biomass-derived activated carbon Spectrophotometry Spirulina platensis

Constraint Selection in Optimization-Based Controllers

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arXiv 2025年

作者： Lee, Haejoon Rousseas, Panagiotis Panagou, Dimitra Department of Robotics University of Michigan Ann ArborMI United States Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Aerospace Engineering University of Michigan Ann ArborMI United States

Human-machine collaboration often involves constrained optimization problems for decision-making processes. However, when the machine is a dynamical system with a continuously evolving state, infeasibility due to multiple conflicting constraints can lead to dangerous outcomes. In this work, we propose a heuristic-based method that resolves infeasibility at every time step by selectively disregarding a subset of soft constraints based on the past values of the Lagrange multipliers. Compared to existing approaches, our method requires the solution of a smaller optimization problem to determine feasibility, resulting in significantly faster computation. Through a series of simulations, we demonstrate that our algorithm achieves performance comparable to state-of-the-art methods while offering improved computational efficiency. © 2025, CC BY.

关键词： Lagrange multipliers