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ACS ES&T air 2024年第8期1卷 767-779页

作者： Shahar Tsameret Daniel Furuta Provat Saha Nohhyeon Kwak Aliaksei Hauryliuk Xiang Li Albert A Presto Jiayu Li Department of Mechanical & Aerospace Engineering University of Miami Coral Gables Florida 33146 United States. Center for Atmospheric Particle Studies Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States. Department of Civil Engineering Bangladesh University of Engineering and Technology Dhaka 1000 Bangladesh. Air Monitoring & Source Testing Program Allegheny County Pittsburgh Pennsylvania 15219 United States. South Coast Air Quality Management District Diamond Bar California 91765 United States.

Indoor air quality is critical to human health, as individuals spend an average of 90% of their time indoors. However, indoor particulate matter (PM) sensor networks are not deployed as often as outdoor sensor networks. In this study, indoor PM exposure is investigated via 2 low-cost sensor networks in Pittsburgh. The concentrations reported by the networks were fed into a Monte Carlo simulation to predict daily PM exposure for 4 demographics (indoor workers, outdoor workers, schoolchildren, and retirees). Additionally, this study compares the effects of 4 different correction factors on reported concentrations from the PurpleAir sensors, including both empirical and physics-based corrections. The results of the Monte Carlo simulation show that mean PM exposure varied by 1.5 μg/m or less when indoor and outdoor concentrations were similar. When indoor PM concentrations were lower than outdoor, increasing the time spent outdoors on the simulation increased exposure by up to 3 μg/m. These differences in exposure highlight the importance of carefully selecting sites for sensor deployment and show the value of having a robust low-cost sensor network with both indoor and outdoor sensor placement.

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Experimentation of Integrating Roadmapping and Sci-Fi Prototyping Methods

Experimentation of Integrating Roadmapping and Sci-Fi Protot...

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Portland International Conference on management of engineering and technology (PICMET)

作者： Miwa Nishinaka Kunio Shirahada Yusuke Kishita Dohjin Miyamoto Hirotaka Osawa Sachiko Kiyokawa Hideaki Takeda The Graduate School of Management Kagawa University Takamatsu Kagawa Japan School of Knowledge Science Transformative Knowledge Management Research Area Japan Advanced Institute of Science and Technology (JAIST) Nomi Ishikawa Japan Department of Precision Engineering The University of Tokyo Tokyo Japan Communication in Science and Technology Education and Research Program Hokkaido University Sapporo Japan Faculty of Science and Technology Keio University Yokohama Kanagawa Japan Graduate School of Education The University of Tokyo Tokyo Japan National Institute of Informatics Tokyo Japan

ISBN: (数字)9781890843458

ISBN: (纸本)9798350369137

In 2023, we proposed a hypothetical knowledge management framework that incorporates science fiction prototyping (SFP) into the traditional roadmapping (RM) method to make RM more innovative and create a future beyond what we can currently imagine. Our main objective is to create a new organizational knowledge co-creation method for generating innovative ideas by incorporating humanistic factors utilizing SFP into RM. In the current article, we present the exploratory study we conducted to examine the hypothetical framework. Experimental workshops were held in November 2023 to compare the integrated method, in which SFP is applied to RM, with the original RM method. We followed a crossover design in the workshops and analyzed the results qualitatively and quantitatively following the perspectives proposed in the hypothetical framework. The qualitative analysis revealed successful integration regarding diverse and broader perspectives. The quantitative analysis utilizing Wilcoxon signed rank tests showed that the scores of the integrated method were significantly higher than those of RM for variables evaluating the effectiveness of the integration, while not for variables related to participants' feelings and satisfaction with the workshops, and sustainability. These findings indicate that the integration was successful in terms of its effectiveness as a method, while participants' subjective feelings toward the workshops were not different in both methods. As for sustainability, which requires a long-term perspective, no apparent differences were observed in these short-term workshops.

关键词： Statistical analysis Conferences Knowledge management Sustainable development Creativity

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Factors that Influence E-Satisfaction and Their Impact on Online Purchase Intention of Telemedicine Applications

Factors that Influence E-Satisfaction and Their Impact on On...

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International Conference on Computing, engineering, and Design (ICCED)

作者： Anderes Gui Idris Gautama So Dea Novantia Elfindah Princes Nesti Fronika Sianipar Hasnah Haron Information System Program School of Information Systems Bina Nusantara University Jakarta Indonesia Management Department Binus Business School Bina Nusantara University Jakarta Indonesia Information Systems Management Department Binus Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta Indonesia Food Technology Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia Faculty of Economics and Muamalat Universiti Sains Islam Malaysia Nilai Malaysia

This study embarked on a rigorous examination of the factors driving user satisfaction and usage behavior in the context of telehealth applications. Utilizing a well- structured Google Form survey, distributed through an array of social media platforms, including WhatsApp, Discord, Instagram, and Line, the research gathered 251 responses. The purposive sampling technique was employed to ensure that the data captured the experiences of individuals who had actively engaged with telehealth services. One hypothesis, relating to the influence of Online Reviews, was found to be unsupported. This surprising result suggests that, contrary to expectations, the opinions and reviews shared online do not significantly affect users’ satisfaction or their behavioral decisions in the context of telehealth applications. This finding highlights the need for a more nuanced understanding of the factors influencing user preferences and choices in this rapidly evolving sector. Conversely, other hypotheses examining factors such as Social Influence, Facilitating Conditions, Perceived Reliability, Price Value, and Purchase Intention were substantiated. The positive influence of these factors on customer usage behavior underscores their significance in shaping user experiences and satisfaction within the telehealth ecosystem. Furthermore, the study posits that facilitating conditions should be closely aligned with technological advancements, as this alignment is conducive to the development of enhanced application features. This insight suggests that telehealth providers should continuously innovate and integrate advanced technologies to ensure that the facilitating conditions meet the ever-evolving needs and expectations of users.

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Waste Valorization from Brazilian Nepheline Syenite Processing as a Strategic Approach to Advancing the Circular Economy

SSRN

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SSRN 2023年

作者： Santos, Diego Haltiery Rosa, Laura Pereira Alves, Cleidson Rosa Simão, Lisandro Arcaro, Sabrina Klegues Montedo, Oscar Rubem Raupp-Pereira, Fabiano Graduate Program in Materials Science and Engineering University of the Extreme South of Santa Catarina Criciúma88806-000 Brazil Department of Civil Engineering Federal Institute of Santa Catarina Criciúma88813-600 Brazil Research Group on Sustainability and Waste Management Postgraduate Program in Environmental Technology University of Ribeirão Preto Ribeirão Preto14096-900 Brazil Brazil

The growing disparity between the high extraction of natural resources and low use of waste as alternative mineral resources will aggravate the scarcity of natural reserves. Therefore, the current linear economy model must be converted to sustainable economic models, such as the circular economy. To achieve this transition, it is important that waste recovery strategies are implemented with a continuous search for solutions for these materials. Thus, this study investigates the waste from the processing of nepheline syenite stone, to promote its valorization as an alternative mineral resource. The classification, potentiality, quantity/viability and applicability (CPQvA) criteria are used as tools to aid decision-making for the waste valorization. The environmental, physical, chemical, morphological, and durability characteristics of nepheline syenite waste (NSW) are analyzed. The results showed evidence for the substitution of NSW for up to 100% of fine aggregates and 25% of Portland cement in civil construction. Furthermore, NSW yields recoveries of more than 90% of potassium for use in agriculture, and up to 70% of iron ore for use in steelworks. Therefore, the results indicate that NSW is viable for different applications, contributing to industrial symbiosis and a strategy for advancing the circular economy. © 2023, The Authors. All rights reserved.

关键词： Sustainable development

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PepTune: De Novo Generation of Therapeutic Peptides with Multi-Objective-Guided Discrete Diffusion

arXiv

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arXiv 2024年

作者： Tang, Sophia Zhang, Yinuo Chatterjee, Pranam Department of Biomedical Engineering Duke University United States Management and Technology Program University of Pennsylvania United States Center of Computational Biology Duke-NUS Medical School Singapore Department of Computer Science Duke University United States Department of Biostatistics and Bioinformatics Duke University United States

Peptide therapeutics, a major class of medicines, have achieved remarkable success across diseases such as diabetes and cancer, with landmark examples such as GLP-1 receptor agonists revolutionizing the treatment of type-2 diabetes and obesity. Despite their success, designing peptides that satisfy multiple conflicting objectives, such as target binding affinity, solubility, and membrane permeability, remains a major challenge. Classical drug development and target structure-based design are ineffective for such tasks, as they fail to optimize global functional properties critical for therapeutic efficacy. Existing generative frameworks are largely limited to continuous spaces, unconditioned outputs, or single-objective guidance, making them unsuitable for discrete sequence optimization across multiple properties. To address this, we present PepTune, a multi-objective discrete diffusion model for the simultaneous generation and optimization of therapeutic peptide SMILES. Built on the Masked Discrete Language Model (MDLM) framework, PepTune ensures valid peptide structures with bond-dependent masking schedules and penalty-based objectives. To guide the diffusion process, we propose a Monte Carlo Tree Search (MCTS)-based strategy that balances exploration and exploitation to iteratively refine Pareto-optimal sequences. MCTS integrates classifier-based rewards with search-tree expansion, overcoming gradient estimation challenges and data sparsity. Using PepTune, we generate diverse, chemically modified peptides optimized for multiple therapeutic properties, including target binding affinity, membrane permeability, solubility, hemolysis, and non-fouling for various disease-relevant targets. In total, our results demonstrate that MCTS-guided masked discrete diffusion is a powerful and modular approach for multi-objective sequence design in discrete state spaces. © 2024, CC BY-NC-ND.

关键词： Trees (mathematics)

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Accurate and precise quantum computation of valence two-neutron systems

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Physical Review C 2024年第6期109卷 064305-064305页

作者： Sota Yoshida (吉田聡太) Takeshi Sato (佐藤健) Takumi Ogata (緒方拓巳) Tomoya Naito (内藤智也) Masaaki Kimura (木村真明) Institute for Promotion of Higher Academic Education School of Data Science and Management for Accelerator-based Science RIKEN Wako 351-0198 Japan Graduate School of Engineering Photon Science Center School of Engineering Research Institute for Photon Science and Laser Technology RIKEN Interdisciplinary Theoretical and Mathematical Sciences Program (iTHEMS) RIKEN 2-1 Hirosawa Wako 351-0198 Japan Department of Physics Graduate School of Science

Developing methods to solve nuclear many-body problems with quantum computers is an imperative pursuit within the nuclear physics community. Here, we introduce a quantum algorithm to accurately and precisely compute the ground state of valence two-neutron systems leveraging presently available noisy intermediate-scale quantum devices. Our focus lies on the nuclei having a doubly magic core plus two valence neutrons in the p, sd, and pf shells, i.e., He6, O18, and Ca42, respectively. Our ansatz, quantum circuit, is constructed in the pair-wise form, taking into account the symmetries of the system in an explicit manner, and enables us to reduce the number of qubits and the number of CNOT gates required. The results on a real quantum hardware by IBM Quantum Platform show that the proposed method gives very accurate results of the ground-state energies, which are typically within 0.1% error in the energy for He6 and O18 and at most 1% error for Ca42. Furthermore, our experiments using real quantum devices also show the pivotal role of the circuit layout design, attuned to the connectivity of the qubits, in mitigating errors.

关键词： Nuclear many-body theory Quantum simulation Shell model

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A pretrained transformer model for decoding individual glucose dynamics from continuous glucose monitoring data

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National Science Review 2025年第5期12卷 362-381页

作者： Yurun Lu Dan Liu Zhongming Liang Rui Liu Pei Chen Yitong Liu Jiachen Li Zhanying Feng Lei M.Li Bin Sheng Weiping Jia Luonan Chen Huating Li Yong Wang Center for Excellence in Mathematical Sciences National Center for Mathematics and Interdisciplinary Sciences Hua Loo-Keng Center for Mathematical Sciences Key Laboratory of Management Decision and Information System Academy of Mathematics and Systems ScienceChinese Academy of Sciences School of Mathematics University of Chinese Academy of SciencesChinese Academy of Sciences Department of Endocrinology and Metabolism Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai Diabetes InstituteShanghai Clinical Center for Diabetes Shanghai Key Laboratory of Diabetes Mellitus Key Laboratory of Systems Health Science of Zhejiang Province School of Life ScienceHangzhou Institute for Advanced StudyUniversity of Chinese Academy of Sciences BGI-Research School of Mathematics South China University of Technology Department of Statistics Department of Biomedical Data Science Bio-X ProgramStanford University Department of Computer Science and Engineering Shanghai Jiao Tong University State Key Laboratory of Cell Biology Center for Excellence in Molecular Cell Science Shanghai Institute of Biochemistry and Cell Biology Chinese Academy of Sciences Guangdong Institute of Intelligence Science and Technology Pazhou Laboratory (Huangpu)

Continuous glucose monitoring(CGM) technology has grown rapidly to track real-time blood glucose levels and trends with improved sensor accuracy. The ease of use and wide availability of CGM will facilitate safe and effective decision making for diabetes management. Here, we developed an attention-based deep learning model, CGMformer, pretrained on a well-controlled and diverse corpus of CGM data to represent individual's intrinsic metabolic state and enable clinical applications. During pretraining, CGMformer encodes glucose dynamics including glucose level, fluctuation, hyperglycemia, and hypoglycemia into latent space with self-supervised learning. It shows generalizability in imputing glucose value across five external datasets with different populations and metabolic states(MAE = 3.7 mg/d L). We then fine-tuned CGMformer towards a diverse panel of downstream tasks in the screening of diabetes and its complications using task-specific data, which demonstrated a consistently boosted predictive accuracy over direct fine-tuning on a single task(AUROC = 0.914 for type 2 diabetes(T2D) screening and 0.741 for complication screening). By learning an intrinsic representation of an individual's glucose dynamics,CGMformer classifies non-diabetic individuals into six clusters with elevated T2D risks, and identifies a specific cluster with lean body-shape but high risk of glucose metabolism disorders, which is overlooked by traditional glucose measurements. Furthermore, CGMformer achieves high accuracy in predicting an individual's postprandial glucose response with dietary modelling(Pearson correlation coefficient = 0.763)and helps personalized dietary recommendations. Overall, CGMformer pretrains a transformer neural network architecture to learn an intrinsic representation by borrowing information from a large amount of daily glucose profiles, and demonstrates predictive capabilities fine-tuned towards a broad range of downstream applications, holding promise for the ear

关键词： pretrained model diabetes continuous glucose monitoring glucose dynamics

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AGENT-BASED SIMULATION OF HURRICANE RISK INFORMATION DISSEMINATION 37

AGENT-BASED SIMULATION OF HURRICANE RISK INFORMATION DISSEMI...

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37th International Conference on Coastal engineering, ICCE 2022

作者： Yeates, Elissa M. Chen, Chen Lindell, Michael K. Shao, Wanyun Harris, Ce'Ne Cass, Evan Coastal and Hydraulics Laboratory US Army Corps of Engineers VicksburgMS39180 United States Fire and Emergency Management Program Division of Engineering Technology Oklahoma State University StillwaterOK74078 United States Department of Urban Design and Planning University of Washington SeattleWA98195 United States Department of Geography The University of Alabama TuscaloosaAL35401 United States Department of Psychology Jackson State University JacksonMS39217 United States

ISBN: (纸本)9780989661164

The effectiveness of official warning dissemination and interpretation determines the adoption of protective actions in response to hurricane threat. This paper describes the development of a conceptual warning diffusion model that articulates the whole process of the hurricane warning diffusion and individual decision-making, drawing on emergency management and social science bodies of literature. This conceptual model is then partially encoded into a NetLogo agent-based simulation model to demonstrate the effects of various warning diffusion components on evacuation decisions for areas of interest. The translation of the conceptual model into agent-based simulations can inform the coastal engineering and science communities of the importance of communicating risk information to the public, and also helps to identify future research needed to illuminate hurricane risk communication pathways. © 2023 American Society of Civil Engineers (ASCE). All rights reserved.

关键词： Hurricanes

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Exploring ERP User Behaviour in Developing Countries: Integrating Self-efficacy and UTAUT Perspectives 5

Exploring ERP User Behaviour in Developing Countries: Integr...

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5th International Conference on Advancement in Data Science, E-Learning and Information Systems, ICADEIS 2023

作者： Syamsuar, Dedy Oktaharisetia, Muhammad Angga Witarsyah, Deden Luthfi, Ahmad Dell, Peter Permana, Yudistira Sira Antoni, Darius Bina Nusantara University School of Information Systems Information Systems Department Indonesia Universitas Bina Darma Program Pasca Sarjana Palembang Indonesia Telkom University School of Industrial Engineering Bandung Indonesia Islamic University of Indonesia Faculty of Industrial Technology Department of Informatics Indonesia Curtin University School of Management and Marketing Faculty of Business and Law Australia Politeknik Sekayu Teknik Informatika Sekayu Indonesia Universitas Indo Global Mandiri Faculty of Computer Science Palembang Indonesia

ISBN: (纸本)9798350303414

ERP stands for enterprise resource planning. It is an information system that is all rolled into one, is very flexible and adaptable, and optimizes business operations while also centralizing all of the company's data. This study aims to empirically investigate the elements that affect users' intention and usage of enterprise resource planning (ERP). This research incorporates self-efficacy into the unified theory of acceptance and use of technology (UTAUT2). A quantitative technique was taken, and as a result, 143 replies that might be used were effectively collected. After that, the information was put through a structural equation modelling partial least square (SEM-PLS) analysis. According to the findings of this research, self-efficacy appears to have a significant influence on all endogenous variables (EE, BI, and UB), as indicated by t-values of 3.951, 7.573, and 5.492, respectively. In addition, the analysis also indicated that PE (4.317), EE (2.397), and HM (3.084) are likewise statistically and substantively significant to BI. The result shows that the R2 for BI and UB indicate a moderate impact of 0.603 and 0.521, respectively. It is suggested that the model has valuable applications in academic and real-world contexts. © 2023 IEEE.

关键词： Enterprise resource planning

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Development of Simultaneous Quantitative Analytical Method for Three Active Components of Agastache Rugosa in Human Plasma Using Ultra-High-Performance Liquid Chromatography–Tandem Mass Spectrometry

SSRN

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SSRN 2023年

作者： Rinik, Urmi Rahman Kim, Ji Eon Lee, Eunok Kwon, Oran Jung, Byung Hwa Center for Advanced Biomolecular Recognition Korea Institute of Science and Technology Seoul02792 Korea Republic of Division of Bio-medical Science and Technology KIST School University of Science and Technology Daejeon34113 Korea Republic of Department of Nutritional Science and Food Management Graduate Program in System Health Science and Engineering Ewha Womans University Korea Republic of

Abstract: Agastache rugosa contains phenolic compounds and flavonoids, and has been extensively used as a traditional herbal medicine. The major components in Agastache rugosa are rosmarinic acid, tilianin, and acacetin, for which several analytical techniques have been reported. However, these substances have yet to be simultaneously quantified in human plasma. In this study, we aimed to simultaneously determine the three active components of Agastacherugosa in human plasma by developing a reliable quantitative analytical method using ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC-MS/MS). Chromatographic separation of the plasma samples was achieved using an ACQUITY UPLC® BEH C18 column with a gradient mobile phase of water and acetonitrile containing 0.1% formic acid. Mass spectrometric detection was performed using a triple quadrupole tandem mass spectrometer in negative electrospray ionization (ESI−) and multiple reaction monitoring (MRM) modes. The developed quantitative method was validated for the three active components. All three analytes exhibited a linear response over the ranges of 0.5–50 ng/mL for rosmarinic acid, 0.1–20 ng/mL for acacetin, and 0.5–20 ng/mL for tilianin with a weighting factor of 1/x (where x is the concentration). At three quality control (QC) concentration levels (low, medium, and high), including the lower limit of quantitation (LLOQ), acceptable accuracy (±15%) was achieved in the intra- and interday validations. The concentration of rosmarinic acid was highest in plasma. Tilianin and acacetin appeared and were eliminated earlier in the plasma than rosmarinic acid. This study provides a successfully validated method that can be used in further clinical applications of Agastache rugosa extracts. © 2023, The Authors. All rights reserved.

关键词： Mass spectrometers

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