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8th International Conference on Modelling and Development of Intelligent Systems, MDIS 2022

作者： Marcu, Stefan-Bogdan Mi, Yanlin Yallapragada, Venkata V. B. Tangney, Mark Tabirca, Sabin School of Computer Science and Informational Technology University College Cork Cork Ireland Faculty of Mathematics and Informatics Transilvania University of Braşov Braşov Romania Cancer Research@UCC APC Microbiome Ireland SynBioCentre iEd Hub University College Cork Cork Ireland Centre for Advanced Photonics and Process Analytics Munster Technological University Cork Ireland

ISBN: (纸本)9783031270338

This paper tackles the problem of assembling a jigsaw puzzle, starting only from a picture of the scrambled jigsaw puzzle pieces on a random, textured background. This manuscript discusses previous approaches in dealing with the jigsaw puzzle problem and brings two contributions: an open source tool for creating realistic scrambled jigsaw puzzles meant to serve as a foundation for further research in the field;and an end to end AI based solution taking advantage of the convolutional neural network architecture, capable of solving a scrambled jigsaw puzzle of unknown pictorial and with an unknown, uniformly textured, background. The lessons and techniques learned in engaging with the jigsaw puzzle problem can be further used in approaching the more general and complex problem of Protein-Protein interaction prediction. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Deep neural networks

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Ai-Driven Electricity Consumption Forecasting for Sustainable Energy Policy: An Svr Time-Series Algorithm in Sparse Data Environments

SSRN

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SSRN 2023年

作者： Liang, Chuan Zun Jie, Ong Shao Hin, Tham Yim Zain, Siti Nur Syamimi Binti Mat Rashid, Yunalis Amani Binti Abdul Kamarudin, Ainur Naseiha Binti Statistics & Data Analytics Cluster Centre for Mathematical Sciences Universiti Malaysia Pahang Al-Sultan Abdullah Lebuh Persiaran Tun Khalil Yaakob Pahang Kuantan26300 Malaysia Faculty of Chemical and Process Engineering Technology Universiti Malaysia Pahang Al-Sultan Abdullah Lebuh Persiaran Tun Khalil Yaakob Pahang Kuantan26300 Malaysia

Rapid population growth, urban expansion, and technological advancements have led to a significant rise in electricity consumption. However, heavy reliance on thermal power generation from fossil fuels has become a major contributor to climate change. To promote clean energy transition and sustainable development, effective electricity management and accurate short-term consumption forecasting are crucial. This article aims to formulate an improvised artificial intelligence (AI) time-series algorithm for predicting annual electricity consumption in Malaysia, particularly in a sparse dataset, utilizing Cross Industry Standard process for Data Mining (CRISP-DM) methodology. The formulated SVR-based time-series algorithm was evaluated utilizing a dataset spanning 1978-2020. The empirical analysis results conveyed that the formulated Support Vector Regression-based (SVR-based) time-series with [[EQUATION]]-insensitive loss function based on the third-degree polynomial kernel outperformed the other 71 SVR-based algorithms considered in this article. In summary, the formulated SVR-based time-series algorithm demonstrates higher accuracy and applicability to the sparse dataset. Moreover, the insightful predictive results acquired from the formulated AI time-series algorithm could be of principal benefit to policymakers in establishing more effective regulations and undertaking actions. These actions align with the Sustainable Development Goals (SDGs) and can be beneficial to humans, society, the economy, and the environment. © 2023, The Authors. All rights reserved.

关键词： Sustainable development

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Absorption and Dispersion: In Search of a Versatile Spectroscopic Technique

arXiv

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arXiv 2024年

作者： Gazizov, Iskander Pinto, Davide Moser, Harald Sam, Savda Martín-Mateos, Pedro O’Faolain, Liam Lendl, Bernhard Institute of Chemical Technologies and Analytics TU Wien Vienna1060 Austria Institute for Quantum Electronics Department of Physics ETH Zürich Zürich8093 Switzerland Centre for Advanced Photonics and Process Analysis Munster Technological University Cork BishopstownT12 P928 Ireland Electronics Technology Department Universidad Carlos III de Madrid Leganés Madrid28911 Spain

This paper investigates three spectroscopic techniques — Tunable Diode Laser Absorption Spectroscopy (TDLAS), Wavelength Modulation Spectroscopy (WMS), and Heterodyne Phase Sensitive Dispersion Spectroscopy (HPSDS) — to evaluate their performance in detecting carbon monoxide (CO) in nitrogen in a 31 m Herriot cell using an Interband Cascade Laser (ICL) emitting at 4559 nm. With the developed spectrometer, we can switch between the techniques with minimal hardware modifications. Calibration curves were established using simple peak-to peak values from the recorded TDLAS, WMS and HSPDS spectra as well as after applying respective spectral models of the sensor responses followed by least square fitting approach. We compare the results when using the different techniques with respect to obtained linearity, minimum detectable value (MDV), standard deviation of the method (sx0), coefficient of variation of the method (Vx0), limit of detection (LOD), and Allan-Werle deviation analysis. The results show significant differences in the performance of the three techniques when establishing calibration curves based on peak-to-peak evaluation of the recorded spectra. However, when establishing model-based calibration curves a more uniform performance of the investigated techniques was found. The results demonstrate that TDLAS is a straightforward and robust technique but has a limited measurement range of up to 65 ppm. WMS offers a linear range of up to 100 ppm if an appropriate spectral model is applied, and a baseline-free operation but requires careful calibration. HPSDS stands out for its wide linear range of up to 100 ppm and immunity to power fluctuations. However, its operation requires a complex mathematical model and radio frequency (RF) components. Allan-Werle deviation analysis demonstrates comparable sensitivities of 0.17 ppb for TDLAS, 0.25 ppb for WMS, and 0.20 ppb for HPSDS. Finally, the minimum detectable value from the calibration curves is 15 ppb for TDLAS, 13

关键词： Absorption spectroscopy

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Insights towards an agile enterprise

Insights towards an agile enterprise

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2020 IEEE International Conference on Engineering, technology and Innovation, ICE/ITMC 2020

作者： Golob, Matic Flores, Dr Myrna Al-Ashaab, Dr Ahmed Al-Ashaab, Habbas Herrera, Martin Maklin, Doroteja Lean Analytics Association Cambridge United Kingdom College of Management of Technology Epfl Lausanne Switzerland Sustainable Manuf. Systems Centre Cranfield University Cranfield United Kingdom Keele University Keele United Kingdom Process and It Cemex Monterrey Mexico

ISBN: (纸本)9781728170374

The meaning and positive impact of agility in software development are generally recognized. However, the benefits of agility as a business strategy in which enterprises design their organization, processes, products, and services in such a way that they can thrive in a continuously changing and unpredictable business environment, have not yet been fully proven. Therefore, a research project was carried out seeking to investigate the actions taken, challenges and benefits of organizations investing efforts to transform into agile enterprises. The aim of this paper is to share: 1) the key foundations and expected benefits of becoming an agile enterprise through a literature review, 2) a summary of the insights and state of the art of the agile enterprise implementation obtained from a global online survey applied to different industries, and 3) the outcomes from a one-day hackathon where teams, comprised of practitioners and students, were challenged to provide prototypes of conceptual solutions to become an agile enterprise. © 2020 IEEE.

关键词： Software design

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Classifying green teas with near infrared hyperspectral imaging

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NIR news 2019年第1-2期31卷 20 - 23页

作者： Puneet Mishra Alison Nordon WestCHEM Department of Pure and Applied Chemistry and Centre for Process Analytics and Control Technology University of Strathclyde Glasgow UK

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Insights towards an agile enterprise

Insights towards an agile enterprise

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International Conference on Concurrent Enterprising

作者： Matic Golob Myrna Flores Ahmed Al-Ashaab Habbas Al-Ashaab Martin Herrera Doroteja Maklin Lean Analytics Association Cambridge UK College of Management of Technology EPFL Lausanne Switzerland Sustainable Manuf. Systems Centre Cranfield University Cranfield UK Keele University Keele UK Process and IT CEMEX Monterrey Mexico

ISBN: (数字)9781728170374

ISBN: (纸本)9781728170381

关键词： Companies Software Technological innovation Bibliographies Industries

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Pocket-size near-IR spectrometers for rapid examination of contaminated textile fibres at the crime-scene

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Vibrational Spectroscopy 2022年 123卷

作者： Rashed, Hamad S. Parrott, Andrew J. Nordon, Alison Baker, Matthew J. Palmer, David S. Department of Pure and Applied Chemistry University of Strathclyde Technology and Innovation Centre 99 George Street GlasgowG1 1RD United Kingdom Trace Evidence Section General Department of Forensic Science and Criminology Dubai Police GHQ Dubai United Arab Emirates Department of Pure and Applied Chemistry and Centre for Process Analytics and Control Technology University of Strathclyde Royal College Building 204 George Street GlasgowG1 1XW United Kingdom Department of Pure and Applied Chemistry University of Strathclyde Thomas Graham Building 295 Cathedral Street GlasgowG1 1XL United Kingdom School of Medicine Faculty of Clinical and Biomedical Sciences University of Central Lancashire Fylde Rd PrestonPR1 2HE

In a typical forensic investigation, fabric analysis plays a vital role in solving different crimes. Several types of textile fibre materials (cotton, polyester, denim, polypropylene, polycotton, and viscose) were analysed in the presence of common contaminants (blood, rainwater, seawater, sand and gunshot-residue) to evaluate the performance of two NIR spectrometers for in situ analysis of different crime scene conditions. The spectrometers used were SCIO® by Consumer Physics and NIRscan Nano by Texas Instruments. The SCIO instrument covers the third overtone region (740–1070 nm) and NIRscan Nano instrument covers the first and second overtone regions (900–1700 nm). Spectra from both instruments were pre-processed using the PRFFECTv2 software to eliminate noise and smooth the data for classification model construction. The models showed high accuracy, sensitivity and specificity with a range of 69–100% for binary classification (one class versus others) and range of 76–100% for multi-class classification of fibre material. This study shows for the first time the capability of pocket-size spectrometers coupled with random forest models for classification of fibre material in the presence of common contaminants in a rapid and non-destructive manner, and so is suitable for investigation of crime scenes. © 2022 The Authors

关键词： Spectrometers

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Quality by digital design to accelerate sustainable medicines development

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International Journal of Pharmaceutics 2025年

作者： Chantal L. Mustoe Alice J. Turner Stephanie J. Urwin Ian Houson Helen Feilden Daniel Markl Mohammed M. Al Qaraghuli Magdalene W.S. Chong Murray Robertson Alison Nordon Blair F. Johnston Cameron J. Brown John Robertson Claire Adjiman Hannah Batchelor Brahim Benyahia Massimo Bresciani Christopher L. Burcham Javier Cardona Ciro Cottini Alastair J. Florence CMAC University of Strathclyde Glasgow G1 1RD United Kingdom Strathclyde Institute of Pharmacy & Biomedical Science University of Strathclyde Glasgow G4 0RE United Kingdom WestCHEM Department of Pure and Applied Chemistry and Centre for Process Analytics and Control Technology (CPACT) University of Strathclyde Glasgow G1 1XL United Kingdom Department of Chemical Engineering Sargent Centre for Process Systems Engineering Imperial College London London SW5 2AZ United Kingdom Department of Chemical Engineering Loughborough University Loughborough LE11 3TU United Kingdom Eli Lilly and Company Lilly Corporate Center Indianapolis IN 46285 USA Department of Chemical & Process Engineering University of Strathclyde Glasgow G1 1XJ United Kingdom Chiesi Farmaceutici S.p.A. Parma Italy

We present a shared industry-academic perspective on the principles and opportunities for Quality by Digital Design (QbDD) as a framework to accelerate medicines development and enable regulatory innovation for new medicines approvals. This approach exploits emerging capabilities in industrial digital technologies to achieve robust control strategies assuring product quality and patient safety whilst reducing development time/costs, improving research and development efficiency, embedding sustainability into new products and processes, and promoting supply chain resilience. Key QbDD drivers include the opportunity for new scientific understanding and advanced simulation and model-driven, automated experimental approaches. QbDD accelerates the identification and exploration of more robust design spaces. Opportunities to optimise multiple objectives emerge in route selection, manufacturability and sustainability whilst assuring product quality. Challenges to QbDD adoption include siloed data and information sources across development stages, gaps in predictive capabilities, and the current extensive reliance on empirical knowledge and judgement. These challenges can be addressed via QbDD workflows; model-driven experimental design to collect and structure findable, accessible, interoperable and reusable (FAIR) data; and chemistry, manufacturing and control ontologies for shareable and reusable knowledge. Additionally, improved product, process, and performance predictive tools must be developed and exploited to provide a holistic end-to-end development approach.

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How resistant is anammox biofilm against antibiotics: A special insight into anammox response towards fluoroquinolones

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Heliyon 2025年第1期11卷 e41339页

作者： Mamun, Faysal-Al Kumar, Rohit Anwuta, Kelvin Ugochukwu Das, Sovik Jaagura, Madis Herodes, Koit Kyrpel, Tetyana Borzyszkowska, Agnieszka Fiszka Zielińska-Jurek, Anna Vincevica-Gaile, Zane Burlakovs, Juris Krauklis, Andrey E. Azra, Mohamad Nor Salauddin, Md Zhong, Jiexi Tenno, Taavo Bester, Kai Zekker, Ivar Institute of Chemistry University of Tartu 14a Ravila St. Tartu 50411 Estonia Indian Institute of Technology Delhi Hauz Khas New Delhi 110 016 India Institute of Genomics University of Tartu Riia 23b Tartu 51010 Estonia Institute of Chemistry Chair of Analytics University of Tartu 14a Ravila St. Tartu 50411 Estonia Department of Environmental Toxicology Faculty of Health Sciences Medical University of Gdansk Dębowa Str. 23A Gdansk 80-204 Poland Department of Process Engineering and Chemical Technology Gdansk University of Technology Narutowicza 11/12 Gdansk 80-233 Poland Department of Environmental Science University of Latvia Jelgavas Street 1 Riga LV-1004 Latvia Faculty of Civil and Mechanical Engineering Riga Technical University Riga LV-1048 Latvia ASEMlab – Laboratory of Advanced and Sustainable Engineering Materials Department of Manufacturing and Civil Engineering NTNU – Norwegian University of Science and Technology Gjøvik 2815 Norway Institute of Climate Adaptation and Marine Biotechnology Universiti Malaysia Terengganu Terengganu Kuala Nerus 21030 Malaysia UCD Dooge Centre for Water Resources Research School of Civil Engineering University College Dublin Ireland Department of Environmental Science Aarhus University Frederiksborgvej 399 Roskilde 4000 Denmark WATEC – Centre for Water Technology Aarhus University Ny Munkegade 120 Aarhus 8000 Denmark

Elevated concentrations of pharmaceutically active compounds (PhACs) in the water bodies are posing a serious threat to the aquatic microbiota and other organisms. In this context, anaerobic ammonium oxidizing (anammox) bacteria carry a great potential to degrade PhACs through their innate metabolic pathways. This study investigates the influence of short-term exposure to lower and higher concentrations (0.8 mg L⁻¹, 0.06 mg L⁻¹, respectively) of antibiotics on the anammox process under distinct operational conditions (starvation/non-starvation) in moving bed biofilm reactor (MBBR). During batch operations that lasted for up to 6 h, the total nitrogen removal efficiency (TNRE) and total nitrogen conversion rate (TNCR) reached a maximum of 93 ± 5 % and 6.97 ± 1.30 mg N g⁻¹ TSS d⁻¹, respectively. Evidently, at higher PhAC levels, the anammox process was active, and up to 75 % PhAC removal efficiency was obtained within 6 h of the batch cycle. Most importantly, the anammox biofilm effectively eliminated the PhACs compounds, i.e., ciprofloxacin (CIP), ofloxacin (OFL), and norfloxacin (NOR) present at higher (0.8 mg L⁻¹) and lower (0.06 mg L⁻¹) total PhACs (sum of CIP, NOR, OFL) concentrations. Furthermore, 16S rRNA sequencing analyses showed a mixture of nitrifying, denitrifying, and anammox bacterial commodities enriched on the carriers' surface with a high relative abundance of Candidatus Brocadia, primarily responsible for catalyzing the anammox process. This study showed the intricate relationship between PhAC concentrations, TNCR, and antibiotic elimination in the wastewater treatment, and the results obtained set up a new breakthrough in wastewater treatment. Future research should investigate the mechanisms that underlie the anammox biofilms' resistance to various types of PhACs and investigate the long-term stability and scalability of this process with real wastewater influents. © 2024

关键词： Adsorption Anammox Moving bed biofilm reactor Nitrogen removal Pharmaceutically active compounds

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Moving Chemistry from Bench to Market: An Introduction to the Agricultural and Food Chemistry Technical Program at the 260th American Chemical Society Fall 2020 Virtual Meeting & Expo

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JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2021年第45期69卷 13255-13259页

作者： Mitchell, Alyson Wu, Changqing Chun, Hyang Sook Beauchamp, Jonathan Jackson, Lauren Yu, Liangli Lucy Liu, Linshu Sarker, Majher Appell, Mike Leibowitz, Sarah Ebeler, Susan Shao, Tony He, Xiaohua Fan, Xuetong Kim, Youngmok Department of Food Science and Technology University of California Davis Davis California 95616 United States Department of Animal & Food Science University of Delaware Newark Delaware 19716 United States School of Food Science and Technology Chung-Ang University Ansung Gyounggi 456-756 Republic of Korea Department of Sensory Analytics Fraunhofer Institute for Process Engineering and Packaging IVV 85354 Freising Germany National Center for Food Safety and Technology (NCFST) United States Food and Drug Administration Summit-Argo Illinois 60501 United States Department of Nutrition and Food Science University of Maryland College Park Maryland 20742 United States Eastern Regional Research Center Agricultural Research Service (ARS) United States Department of Agriculture (USDA) Wyndmoor Pennsylvania 19038 United States Mycotoxin Prevention and Applied Microbiology Research Unit National Center for Agricultural Utilization Research Agricultural Research Service (ARS) United States Department of Agriculture (USDA) Peoria Illinois 61604 United States DeLaval Incorporated Kansas City Missouri 64153 United States PepsiCo Incorporated Plano Texas 75024 United States Western Regional Research Center Agricultural Research Service (ARS) United States Department of Agriculture (USDA) Albany California 94710 United States Finlays The Analytical and Research Centre (ARC) North Kingstown Rhode Island 02852 United States

This is the second special issue of the Journal of Agricultural and Food Chemistry (JAFC) that reviews the Agricultural and Food Chemistry Division (AGFD) technical program from a national meeting of the American Chemical Society (ACS). The 260th meeting was virtually held on August 17-20, 2020 as a result of the COVID-19 pandemic. Although it was the first-ever all online meeting in ACS history, a total of 311 abstracts were submitted to the AGFD technical program for oral and poster presentations and 34 technical sessions were held in 22 symposia, which covered a broad range of food and agricultural topics. The very first virtual ACS meeting was successful with the high quality of presentations, the number of online audiences, and seamless technology.

关键词： Food Plant derived food Safety Bacteria Quality management

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