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15th Greenhouse Gas control Technologies Conference, GHGT 2021

作者： Garcia, Susana Smit, Berend Reimer, Jeffrey A. Anantharaman, Rahul Bardow, André School of Engineering and Physical Sciences Heriot-Watt University EdinburghEH14 4AS United Kingdom LausanneCH-1015 Switzerland Department of Chemical and Biomolecular Engineering University of California Berkeley BerkeleyCA United States Materials Science Division Lawrence Berkeley National Laboratory BerkeleyCA United States SINTEF Energy Research Sem Sælandsvei 11 TrondheimNO-7465 Norway Energy and Process Systems Engineering ETH Zurich Zurich Switzerland

The PrISMa ("process-Informed designed of tailor-made sorbent materials for energy efficient carbon capture") project is an international effort funded through the ACT programme (Accelerating CCS Technologies, Horizon2020 Project No 294766). It accelerates the transition of energy and industrial sectors to a low-carbon economy by developing a technology platform to tailor-make cost-efficient carbon capture solutions for a range of different CO2 sources and CO2 use/destinations. This platform will guarantee an optimal separation in terms of an effective carbon price (ECP) that makes a particular process economically viable and environmentally beneficial. To achieve this aim, PrISMa integrates materials and process design, supported by computational materials genomic approaches, life cycle analysis, machine-learning, high-throughput material synthesis and characterization, device-performance testing, value chain analysis and systematic process design. In addition, PrISMa aims to initiate a systematic thinking about efficient solutions to mitigate CO2 emissions from different local CO2 sources that are optimal for a specific local setting. In such a setting the impact of PrISMa will be significant as the need for tailor-made solutions will be increasingly important if CO2 mitigation at the local level becomes the norm. The PrISMa platform allows for high-throughput screening of materials to maximise their impact, enables the design of efficient pilot-scale test facilities with improved processes under real conditions and, decreases the time to market of affordable, cost-competitive, low environmental impact, and resource-efficient advanced capture technologies. Through the integration of materials design, process design and environmental considerations, we change the paradigm on how novel materials are developed for carbon capture applications. © 2021 15th Greenhouse Gas control Technologies Conference 2021, GHGT 2021. All Rights Reserved.

关键词： Genome

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A System for Elemental Analysis of Aluminum Chips, based on Neutron Activation Analysis

A System for Elemental Analysis of Aluminum Chips, based on ...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： T. Szczesniak M. Grodzicka-Kobylka K. Brylew L. Adamowski K. Grodzicki L. Janiak A. Dziedzic M. Sitek A. Syntfeld-Kazuch H. Zastawny A. Gajderowicz F. Peregrin T. Baldi M. da Silva Lopez M. J. Neuer B. Kleimt Radiation Detectors and Plasma Diagnostics Division (TJ3) National Centre for Nuclear Research (NCBJ) Otwock Poland Industrial Process Control Systems SYSKON Wroclaw Poland Nuclear Technology Centre in Wroclaw POLON Wroclaw Poland GRUPAL ART. S.L. Aluminum Refinery Barcelona Spain The Technology Centre of Catalonia EURECAT Barcelona Spain innoRIID GmbH Grevenbroich Germany VDEh-Betriebsforschungsinstitut (BFI) Dusseldorf Germany

The performance of the demonstrator of the system for elemental analysis of aluminum chips is presented. The system is based on neutron activation analysis and isotopic neutron source of PuBe emitting 2x10^6 n/s. The detection system comprises of large 3.5x8 inch LaBr scintillators with an option of easy change to 5x10 inch NaI(Tl) or 5x5 inch BGO. The industrial samples under study are constantly moving through a vertical pipe in a closed loop system which mimics the industrial conditions at aluminum refinery. The system performance is presented in relation to the recorded gamma spectra and gamma lines characteristic for the following chemical elements: Al, Cr, Cu, Fe, Mg, Mn, Ni, Pb, Si, Ti, Zn. The efficiency of gamma spectra detection in the proposed setup is also discussed in relation to the applied detectors and physical limits of neutron activation methods. The results are compared to the standard industrial analysis based on spark optical emission spectroscopy and multiple sample collection.

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Longitudinal monitoring and prediction of long-term outcome of scar stiffness on pediatric patients

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Burns & Trauma 2021年第1期9卷 196-206页

作者： Bettina Müller Edoardo Mazza Clemens Schiestl Julia Elrod Institute for Mechanical Systems Department of Mechanical and Process EngineeringETH ZurichLeonhardstrasse 218092 ZurichSwitzerland Empa Swiss Federal Laboratories for Materials Science and TechnologyUeberlandstrasse 1298600 DübendorfSwitzerland Burn Center Division of Plastic and Reconstructive SurgeryUniversity Children’s Hospital ZurichSteinwiesstrasse 758032 ZürichSwitzerland Children’s Research Center(CRC) University Children’s Hospital ZurichSteinwiesstrasse 758032 ZürichSwitzerland

Background:Hypertrophic scarring after burn injury is one of the greatest unmet challenges in patients with burn injuries.A better understanding of the characteristics of scar maturation and early prediction of the long-term outcome of scarring are prerequisites for improving targeted therapies and pivotal for patient ***:Repeated measurements of scar stiffness in 11 pediatric patients were performed over the course of 1 year using 2 suction devices,the Cutometer and the *** addition,the observer pliability score of the Patient and Observer Scar Assessment Scale was *** longitudinal study allowed quantification of the ability of each of the measured parameters to reflect scar maturation,as indicated by change in skin pliability/stiffness,over time(using linear regression);the ability to distinguish individual patients(intraclass correlation coefficient(ICC));the correlation of the devices(Spearman correlation coefficient);and the ability to predict longterm scar maturation based on early scar assessment(using receiver operating characteristic).Results:All the tools used showed significant longitudinal decrease of scar stiffness from 3 months until 12 months after the *** Nimble(ICC_(patient)^(Nimble)=0.99)and the Cutometer(ICC_(patient)^(Cuto)=0.97)demonstrated an excellent ability to distinguish between individual *** Nimble seemed to be able to predict the 12-month pliability of scars based on early(3-month)measurements(area under the curve(AUC)_(12m)^(POSAS)=0.67;AUC_(12m)^(C)=0.46;AUC_(12m)^(N)=0.79).Conclusions:The results of this preliminary study suggest that all 3 tools provide suitable means to quantify alterations in scar stiffness over *** evidence suggests the Nimble is most favorable for predicting changes in stiffness associated with long-term scar *** studies with a larger sample size are required to validate tissue suction as a clinical tool for analysis of changes of scar stiffne

关键词： Pediatric burns Scar maturation POSAS Cutometer Nimble

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Closed-loop Scheduling in a canned food factory

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IFAC-PapersOnLine 2020年第2期53卷 10791-10796页

作者： C.G. Palacín C. Vilas A.A. Alonso José L. Pitarch C. de Prada Systems engineering and Automatic Control Dpt. University of Valladolid Valladolid Spain (Bio)Process engineering Group Instituto de Investigaciones Marinas (CSIC) Vigo Spain

This paper addresses the problem of closed-loop operation of scheduling, together with the interaction of control and scheduling, for a class of processes that appear very often in industry: those that combine continuous production lines with parallel batch units that share some resources. The paper presents a novel approach to this problem, including batching and a new type of precedence in the assignment problem. It also considers the effect of shared resources on the duration of the cycle time of the batch units. The approach is illustrated with a real-life example of a canned tuna factory

关键词： Integration of scheduling control shared resources tuna cans sterilisation process optimisation continuous-batch process scheduling

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Multi-objective Optimization, Techno-economic Analysis, and Life Cycle Assessment of an Innovative Solar-Biomass-Driven Cogeneration System Integrated with MED-RO-MD: A Case Study of the Canary Islands

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Renewable Energy 2025年

作者： Seyed Alireza Mousavi Rabeti Mohammad Hasan Khoshgoftar Manesh Ana María Blanco-Marigorta B. Del Río-Gamero Energy Environment and Biological Systems Research Lab (EEBRlab) Division of Thermal Sciences and Energy Systems Department of Mechanical Engineering Faculty of Technology & Engineering University of Qom Qom Iran Department of Process Engineering Universidad de las Palmas de Gran Canaria Las Palmas de Gran Canaria Spain

Managing fresh water and electricity production in islands is vital for sustainability and reducing dependency on external resources, ensuring energy security and environmental protection. This study explores the design, analysis, and feasibility of an innovative biomass-solar cogeneration system that produces both power and freshwater for the Canary Islands, Spain. The proposed system design incorporates a combination of the Brayton cycle, steam Rankine cycle, and organic Rankine cycle for power generation, while integrating multi-effect distillation, reverse osmosis, and membrane distillation desalination for freshwater production. Additionally, a CO 2 capture unit is included to minimize environmental pollutant emissions. The solar field provides the necessary heat for the system via the solar tower, while the air-steam gasification unit supplies the required energy for the cycle using biomass. The biomass fuel selected is based on the local forest type, specifically Canary Pine Needles. Machine learning is applied to analyze the subsystems of the proposed system. The feasibility of the proposed system has been evaluated through technical-economic analysis and life cycle assessment. Dynamic modeling was performed based on the climatic conditions of Las Palmas. Finally, a sensitivity analysis and multi-objective optimization were conducted on the system's functional parameters. The objective functions in the optimization process included maximizing cogeneration efficiency, minimizing the payback period, and minimizing the total environmental impact rate. Three multi-objective optimization algorithms (NSGA-III, MOMVO, MOGOA) were used to optimize the proposed system. The results indicate that the proposed system achieves an average energy efficiency of 31.64% and exergy efficiency of 14.35% annually. The average levelized cost and environmental impact of electricity are calculated to be 0.19 $/kWh and 1.24 mPts/kWh, respectively. Additionally, the payback period fo

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Recursive Weighted Null-Space Fitting Method for Identification of Multivariate systems ⁎

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IFAC-PapersOnLine 2021年第7期54卷 345-350页

作者： Mengyuan Fang Miguel Galrinho Håkan Hjalmarsson Zhejiang Engineering Laboratory of Industrial Internet Communication Technology Zhejiang Sci-Tech University Hangzhou China. State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China OHB Sweden AB Kista Sweden Centre for Advanced Bio Production and Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden

Recursive identification of structured multivariate models is known to be difficult due to the general non-convexity of the likelihood function. In this work, we propose a recursive multivariate weighted null-space fitting method for identification of structured multivariate models. The proposed method first uses recursive least squares to estimate a high order non-parametric model, then a parametric model is obtained through weighted least squares from the non-parametric model. In this way, the method avoids directly optimizing a non-convex likelihood function and has guaranteed global convergency. Moreover, the proposed method is flexible in model structures and has the same finite sample performance as its off-line counterpart. We use simulation examples to illustrate the performance.

关键词： Recursive system identification multivariate systems weighted null-space fitting

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Diagnosis of Lymphatic Metastasis in Breast Cancer Using Nanoparticle Technology-Diagnosis, Therapy, Imaging, Treatment

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Open Neuroimaging Journal 2024年 17卷

作者： De Britto, Novietta Neeraja, R. Anbarasi, L. Jani Ravi, Vinayakumar Syed Ibrahim, S.P. Jawahar, Malathy Al Mazroa, Alanoud North Carolina State University College of Engineering Joint Department of Biomedical Engineering-UNC NC United States School of Computer Science and Engineering Vellore Institute of Technology Chennai India Center for Artificial Intelligence Prince Mohammad Bin Fahd University Khobar Saudi Arabia Leather Process Technology Division CSIR-Central Leather Research Institute Chennai India Department of Information Systems College of Computer and Information Sciences Princess Nourah bint Abdulrahman University (PNU) P.O. Box 84428 Riyadh 11671 Saudi Arabia

Breast cancer is a major cause of patient death rates, frequently leading to life-changing repercussions even after survival is attained. This paper aims to investigate therapeutic alternatives employing nanoparticles to specifically target and treat lymphatic metastasis, which is a highly dangerous characteristic of breast cancer. This work explores the effectiveness and importance of using nanoparticle-based therapeutics to prevent the harmful consequences of breast cancer progression. The paper begins by discussing the progress of lymphatic metastasis and then delves into the use of nanoparticle technology in imaging techniques, diagnostic methods, and therapy tactics. This section provides detailed information on primary targeting treatments, including chemotherapy specifically targeting cancer stem cells, induction of tumour cell death, suppression of Epithelial-Mesenchymal Transition (EMT), manipulation of the Tumour Microenvironment (TME), and improvement of the immune response. In addition, the research explores the use of nanoparticle technology in treatment plans, specifically focusing on its super magnetic capabilities and the application of gold nanoparticles, nanodiamonds, and other related qualities. Nanoparticle technology presents an optimistic strategy to address lymphatic metastasis in breast cancer. Nanoparticles can be used to deliver drugs or therapeutic substances directly to cancerous tumours, specifically targeting cancer cells to either destroy them or slow their growth. This strategy provides a solution for the administration of pharmaceuticals or substances that may provide challenges when delivered using conventional methods. Furthermore, nanoparticles facilitate the visualisation of tumours, aiding healthcare professionals in evaluating the severity of malignancy and formulating suitable treatment strategies. A comprehensive discussion has been conducted on several nanoparticles employed for inhibiting the dissemination of cancer cells f

关键词： Blood-brain barrier Cancer-associated fibroblasts Circulatory tumor cells Extra cellular matrix Metastasis Photo thermal therapy Triple negative breast cancer

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Nonlinear Cooperative Output Regulation with Input Delay Compensation

arXiv

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arXiv 2024年

作者： Zheng, Shiqi Ahn, Choon Ki Jiang, Xiaowei Yan, Huaicheng Shi, Peng The School of Automation China University of Geosciences Wuhan430079 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China The Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China The Shaoyang Institute of Advanced Manufacturing Technology Shaoyang422000 China The School of Electrical Engineering Korea University Seoul136-701 Korea Republic of The Key Laboratory of Smart Manufacturing in Energy Chemical Process of Ministry of Education East China University of Science and Technology Shanghai200237 China The School of Electrical and Mechanical Engineering The University of Adelaide AdelaideSA5005 Australia

This paper investigates the cooperative output regulation (COR) of nonlinear multi-agent systems (MASs) with long input delay based on periodic event-triggered mechanism. Compared with other mechanisms, periodic event-triggered control can automatically guarantee a Zeno-free behavior and avoid the continuous monitoring of triggered conditions. First, a new periodic event-triggered distributed observer, which is based on the fully asynchronous communication data, is proposed to estimate the leader information. Second, a new distributed predictor feedback control method is proposed for the considered nonlinear MASs with input delay. By coordinate transformation, the MASs are mapped into new coupled ODE-PDE target systems with some disturbance-like terms. Then, we show that the COR problem is solvable. At last, to further save the communication resource, a periodic event-triggered mechanism is considered in the sensor-to-controller transmission in every agent. A new periodic event-triggered filter is proposed to deal with the periodic event-triggered feedback data. The MASs with input delay are mapped into coupled ODE-PDE target systems with sampled data information. Then, Lyapunov-Krasovskii functions are constructed to demonstrate the exponential stability of the MASs. Simulations verify the validity of the proposed results. © 2024, CC BY-NC-ND.

关键词： Feedback control

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Zeroth-order algorithms for stochastic distributed nonconvex optimization

arXiv

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arXiv 2021年

作者： Yi, Xinlei Zhang, Shengjun Yang, Tao Johansson, Karl H. Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden Department of Electrical Engineering University of North Texas DentonTX76203 United States State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

In this paper, we consider a stochastic distributed nonconvex optimization problem with the cost function being distributed over n agents having access only to zeroth-order (ZO) information of the cost. This problem has various machine learning applications. As a solution, we propose two distributed ZO algorithms, in which at each iteration each agent samples the local stochastic ZO oracle at two points with a time-varying smoothing parameter. We show that the proposed algorithms achieve the linear speedup convergence rate O(√p=(nT)) for smooth cost functions under the state-dependent variance assumptions which are more general than the commonly used bounded variance and Lipschitz assumptions, and O(p=(nT)) convergence rate when the global cost function additionally satisfies the Polyak-Lojasiewicz (P-L) condition in addition, where p and T are the dimension of the decision variable and the total number of iterations, respectively. To the best of our knowledge, this is the first linear speedup result for distributed ZO algorithms, which enables systematic processing performance improvements by adding more agents. We also show that the proposed algorithms converge linearly under the relative bounded second moment assumptions and the P-L condition. We demonstrate through numerical experiments the efficiency of our algorithms on generating adversarial examples from deep neural networks in comparison with baseline and recently proposed centralized and distributed ZO algorithms. Copyright © 2021, The Authors. All rights reserved.

关键词： Cost functions

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Analysis and control of autonomous mobility-on-demand systems

arXiv

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arXiv 2021年

作者： Zardini, Gioele Lanzetti, Nicolas Pavone, Marco Frazzoli, Emilio Institute for Dynamic Systems and Control Department of Mechanical and Process Engineering ETH Zürich Zürich Switzerland Automatic Control Laboratory Department of Information Technology and ElectricalEngineering ETH Zürich Zürich Switzerland Autonomous Systems Lab Department of Aeronautics and Astronautics Stanford University StanfordCA United States

Challenged by urbanization and increasing travel needs, existing transportation systems need new mobility paradigms. In this article, we present the emerging concept of autonomous mobility-on-demand, whereby centrally orchestrated fleets of autonomous vehicles provide mobility service to customers. We provide a comprehensive review of methods and tools to model and solve problems related to autonomous mobility-on-demand systems. Specifically, we first identify problem settings for their analysis and control, from both operational and planning perspectives. We then review modeling aspects, including transportation networks, transportation demand, congestion, operational constraints, and interactions with existing infrastructure. Thereafter, we provide a systematic analysis of existing solution methods and performance metrics, highlighting trends and trade-offs. Finally, we present various directions for further research. © 2021, CC BY-NC-ND.

关键词： Autonomous vehicles

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