391 research outputs found
Highly efficient macrocycle and cage formation via hindered urea chemistry
No full textU of I OnlyDynamic covalent chemistry (DCC) is a powerful tool that enables the synthesis of novel macrocycles, molecular cages, knots and frameworks, as well as the development of dynamic polymeric materials with unique properties. Hindered urea bond (HUB), a newly developed DCC, has found applications in dynamic materials designs such as self-healing, malleable, shape-memory or environmentally-adaptive materials. However, despite of the intensive research, study of this new, facile dynamic chemistry is still in its infancy. The potential of HUB in the formation of discrete structures in small molecular level is largely overlooked and not demonstrated. What’s more, a turning-off mechanism for HUB was not found which can severally limit the applications of HUB-based materials. Here we report the discovery of acid-assisted de-tert-butylation reaction that can instantly “turn off” the dynamicity of HUB, leading to improved chemical stabilities and mechanical properties of HUB-containing materials. We also demonstrated the use of dynamic HUB for the construction of urea macrocycles with very high efficiency. The bulky N-tert-butyl plays key roles to facilitate the formation of macrocycles, providing not only the kinetic control due to the formation of the cyclization-promoting cis C=O/tert-butyl conformation, but also possibly the thermodynamic stabilization of macrocycles with weak association interactions. Building upon the macrocyclization mechanism, we demonstrated that HUB can function as efficient cyclization enabling motif for cyclic peptides. Beyond macrocycles, HUB was also utilized to efficiently construct a series of structures with different topologies as well as urea cages, which were demonstrated to be able to separate important petrochemicals such as pyridine/toluene and benzene/cyclohexane.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2023-08-01The student, Yingfeng Yang, accepted the attached license on 2021-07-09 at 04:30.The student, Yingfeng Yang, submitted this Dissertation for approval on 2021-07-09 at 05:03.This Dissertation was approved for publication on 2021-07-14 at 15:30.DSpace SAF Submission Ingestion Package generated from Vireo submission #16816 on 2022-01-12 at 12:54:04Made available in DSpace on 2022-01-12T22:35:07Z (GMT). No. of bitstreams: 2
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How to classify microclimates more validly and finely? A novel method for mapping local climate zone (LCZ) on micro-scales
No full textGlobal climate change and rapid urbanization are driving microclimate variations in urban areas, intensifying the formation of urban heat islands (UHIs) vulnerable to extreme weather. The local climate zone (LCZ) framework, using remote sensing (RS) and geographic information system (GIS), has advanced with the World Urban Database and Access Portal Tool (WUDAPT), enabling microclimate understanding for improved urban planning and climate adaptation. However, mapping LCZs at the micro-scale relies on locally available GIS data or RS imagery, data gaps, authenticity issues, and low-resolution imagery often lead to inaccurate microclimate classifications. To enhance the validity and sophistication of microclimate classification, this study introduces a novel method for mapping LCZ using unmanned aerial vehicle (UAV) photogrammetry at the micro-scale (LCZ-UAV-MS), which constructs detailed land use and land cover (LULC) and 3D real scene (3DRS) models, calculates urban surface parameters (USPs) for each basic spatial unit (BSU) through spatial statistical analysis, and employs a decision-making classifier to categorize each BSU. This study validates the proposed method using Gulangyu as the study area, employing image overlay, temperature observation, and expert knowledge, with the following results: 1) Spatial percentage showing 51 % natural environments (LCZ A, B, C, and D), 27 % neutral environments (LCZ 7, 8, 9, 10, and Y), and 22 % built environments (LCZ 1, 2, 3, 4, 5, and 6) in Gulangyu. 2) The variance in mean LST across different LCZs was 1.02 in January and 5.18 in August 2024, with temperature differences more pronounced in summer, where the built environment had a higher mean LST of 41.3 °C compared to 35.2 °C in the natural environment and 38.3 °C in the neutral environment. 3) Field research at 22 random sample sites showed that 95 % of LCZ-UAV-MS classifications matched the field, outperforming WUDAPT LCZ, which matched only 10 %. These demonstrate that the LCZ-UAV-MS accurately captures microclimate temperature variations and provides a more precise micro-scale description than the WUDAPT LCZ. This study bridges the gap of LCZ studies in specific regions and scales, enhances the applicability of the LCZ framework at the micro-scale, and provides technical support for urban blue-green infrastructure management and resilient climate design strategies
Automated Personnel Activities Observation in the Catheterization Laboratory
No full textThis thesis presents a method for personnel activities observation, i.e., 3D human pose estimation and tracking, in a Catheterization Laboratory(Cath Lab). We mount five cameras from different angles in the Cath Lab, where surgeons and assistants are in similar clothes while doing surgery. Accurate 3D human pose estimation is the cornerstone of our method. Most previous 3D pose estimation methods train their models directly on a 3D pose dataset. However, these methods are not suitable for our task: 1) We do not have enough 3D pose data for training because of privacy issues and specificity 2) The model needs to be retrained in different operating rooms or the camera calibration changed. To solve these problems, we decompose the 3D human pose estimation task into two stages, avoiding the need for large amounts of 3D pose data and retraining. In the first stage, we apply YOLOX and HRNet for 2D human detection and 2D pose estimation. Simultaneously, the 2D object tracking network Bytetrack tracks person identities based on detection results. Then we use a matching algorithm to match the corresponding 2D poses from multiple views and reconstruct 3D poses. Given 3D poses and tracking identities, we at last introduce a hybrid method tracking algorithm. By feeding 2D tracking results into the matching and tracking algorithm, we increase the accuracy of the result in a scene where people are wearing similar clothes. We fine-tune and test our method with an operating room dataset. Finally, we validate the method on data from the Cath Lab.Electrical Engineerin
Functional analysis on the interactions of the human immunodeficiency virus type 1 integrase with its cofactors that regulate viral replication
No full textLike all viruses, the replication of HIV-1 relies heavily on host proteins due to its limited genome products. HIV-1 integrase (IN) catalyzes the integration of viral DNA into host genome and also impacts other steps of viral replication cycle, all of which are assisted by various cellular proteins. Among them, LEDGF/p75 acts as the IN-to-chromatin tethering factor. However, whether other cellular cofactors also participate in this process still remains elusive. To gain insight into the mechanism of action of HIV-1 IN during viral integration, we used a previously described IN/yeast lethality system and our results revealed that the HIV-1 IN-induced yeast lethality absolutely required its chromatin binding ability. Since there is no yeast homolog of LEDGF/p75, it raises the possibility that IN may recruit other cellular cofactors for its chromatin targeting. Consistently, further analysis in mammalian cells indicated that HIV-1 IN was able to mediate chromatin binding independent of IN-LEDGF/p75 interaction and that HIV-1 fitness relied more on chromatin binding than LEDGF/p75 binding of IN. These data greatly enrich our current knowledge on the dynamic interplay within the ternary complex IN/LEDGF/chromatin.
HIV-1 exploits multiple cellular cofactors not only to facilitate viral replication, but also to evade the host defense system in favor of the virus. IN is known to be an unstable protein, degraded by the host ubiquitin-proteasome pathway. To investigate how IN avoids the host degradation machinery in the context of viral infection, we showed that IN interacted with host protein Ku70 and protected itself from the Lys48-linked polyubiquitination proteasomal pathway. More importantly, Ku70 was shown to be incorporated into the progeny virus in an IN-dependent manner, and both cell- and virus- associated Ku70 were essential for HIV-1 replication. Finally, the data demonstrated that the interactions between HIV-1 IN and host cofactors can be regulated through its SUMO-interacting motifs (SIMs). Three putative SIMs (72VILV75; 200IVDI203 and 257IKII260) in IN were examined and shown to be essential for IN-LEDGF/p75 but not IN-Ku70 interaction.
In summary, this study advances our knowledge of the interaction network between IN and its cofactors, which would have important implications for the design of anti-HIV drugs.May 201
Optimization of manufacturing systems using the Internet of Things /
No full textOptimization of Manufacturing Systems Using the Internet of Things extends the IoT (Internet of Things) into the manufacturing field to develop an IoMT (Internet of Manufacturing Things) architecture with real-time traceability, visibility, and interoperability in production planning, execution, and control. This book is essential reading for anyone interested in the optimization and control of an intelligent manufacturing system. As modern manufacturing shop-floors can create bottlenecks in the capturing and collection of real-time field information, and because paper-based manual systems are time-consuming and prone to errors, this book helps readers understand how to alleviate these issues, assisting them in their decision-making on shop-floors.Online resource; title from title page (viewed January 4, 2017).Includes bibliographical references and index.Cover; Title page; Copyright page; Contents; Preface; Chapter 1 -- Introduction; 1.1 -- The concept of IoT; 1.2 -- Existing manufacturing paradigms and their limitations; 1.2.1 -- Agile Manufacturing; 1.2.2 -- Networked Manufacturing; 1.2.3 -- Reconfigurable Manufacturing Systems; 1.2.3.1 -- Modularity; 1.2.3.2 -- Integrability; 1.2.3.3 -- Customization; 1.2.3.4 -- Convertibility; 1.2.3.5 -- Scalability; 1.2.3.6 -- Diagnosability; 1.2.4 -- Product-Service System/Industrial Product-Service Systems; 1.2.5 -- Manufacturing Grid; 1.2.6 -- Cloud Manufacturing; 1.2.7 -- Limitations.1.3 -- Applications of IoT in manufacturing system1.4 -- The conception of IoT-MS; 1.5 -- Key features and limitations of IoT-MS; 1.6 -- Organization of the book; References; Chapter 2 -- Overview of IoT-Enabled Manufacturing System; 2.1 -- Introduction; 2.2 -- Related work; 2.2.1 -- Advanced Manufacturing Paradigms and Technologies; 2.2.2 -- Manufacturing Information Standard and Share and Integration Method; 2.3 -- Overall architecture of IoT-MS; 2.4 -- Integration framework of real-time manufacturing information; 2.4.1 -- Framework of Real-Time Manufacturing Information Sharing and Integration.2.4.2 -- Real-Time Manufacturing Data Processing, Sharing, and Exchanging Service2.5 -- The worklogic of IoT-MS; 2.6 -- Description of the core technologies of IoT-MS; References; Chapter 3 -- Real-Time and Multisource Manufacturing Information Sensing System; 3.1 -- Introduction; 3.2 -- Related works; 3.2.1 -- Real-Time Manufacturing Data Capturing; 3.2.2 -- Sensor Management; 3.2.3 -- Manufacturing Information Processing and Sharing; 3.3 -- Overall architecture of real-time and€multisource RMMISS; 3.3.1 -- Deployment of Multiple Sensors; 3.3.2 -- Multiple Sensors Manager.3.3.3 -- Multisource Manufacturing Information Processing and€Sharing3.4 -- Deployment of multisensors; 3.4.1 -- Description of Multisource Manufacturing Information; 3.4.2 -- Multiple Sensors Selection; 3.5 -- Multiple sensors manager; 3.6 -- Multisource manufacturing information capturing and sharing; 3.6.1 -- Data Preprocessing; 3.6.2 -- Information Encapsulation; 3.6.3 -- Manufacturing Information Sharing; 3.7 -- Case study; 3.7.1 -- Hardware Device; 3.7.2 -- Software System; References; Chapter 4 -- IoT-Enabled Smart Assembly Station; 4.1 -- Introduction; 4.2 -- Related works.4.2.1 -- RFID-Based Applications in Assembly Line4.2.2 -- Assistant Services for Assembly Line; 4.3 -- Overall architecture of IoT-enabled smart assembly station; 4.4 -- Real-time status monitoring; 4.5 -- Real-time production guiding; 4.6 -- Real-time production data sharing; 4.7 -- Real-time production requeuing; References; Chapter 5 -- Cloud Computing-Based Manufacturing Resources Configuration Method; 5.1 -- Introduction; 5.2 -- Related works; 5.2.1 -- Cloud Manufacturing; 5.2.2 -- Real-Time Production Information Perception and Capturing; 5.2.3 -- Cloud Service Selection and Composition.5.3 -- Overall architecture of manufacturing resources configuration method.Optimization of Manufacturing Systems Using the Internet of Things extends the IoT (Internet of Things) into the manufacturing field to develop an IoMT (Internet of Manufacturing Things) architecture with real-time traceability, visibility, and interoperability in production planning, execution, and control. This book is essential reading for anyone interested in the optimization and control of an intelligent manufacturing system. As modern manufacturing shop-floors can create bottlenecks in the capturing and collection of real-time field information, and because paper-based manual systems are time-consuming and prone to errors, this book helps readers understand how to alleviate these issues, assisting them in their decision-making on shop-floors.Elsevie
A forward collision avoidance algorithm based on driver braking behavior
No full textMeasuring risk is critical for collision avoidance. The paper aims to develop an online risk level classification algorithm for forward collision avoidance systems. Assuming risk levels are reflected by braking profiles, deceleration curves from critical evasive braking events from the Virginia “100-car” database were first extracted. The curves are then clustered into different risk levels based on spectrum clustering, using curve distance and curve changing rate as dissimilarity metrics among deceleration curves. Fuzzy logic rules of safety indicators at critical braking onset for risk classification were then extracted according to the clustered risk levels. The safety indicators include time to collision, time headway, and final relative distance under emergency braking, which characterizes three kinds of uncertain critical conditions respectively. Finally, the obtained fuzzy risk level classification algorithm was tested and compared with other Automatic Emergency Braking (AEB) algorithms under Euro-NCAP testing scenarios in simulation. Results show the proposed algorithm is promising in balancing the objectives of avoiding collision and reducing interference with driver's normal driving compared with other algorithms.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and Plannin
A Model of Trade and Growth with a Non-traded Service Sector.
No full textThis paper incorporates a nontraded service sector into an otherwise neoclassical model of trade and growth. The author's model can explain why the relative price of services, the expenditure share of services, and the employment share of the service sector all tend to rise with the level of per capita income, which is determined, in the long run, by the ratio of the saving rate to the rate of labor growth and the level of labor-augmenting technical progress. The author also finds that a rich country with a high level of technical progress, ceteris paribus, has comparative advantage in producing capital-intensive goods.
Inner approximation algorithm for generalized linear multiplicative programming problems
No full textAbstract An efficient inner approximation algorithm is presented for solving the generalized linear multiplicative programming problem with generalized linear multiplicative constraints. The problem is firstly converted into an equivalent generalized geometric programming problem, then some magnifying-shrinking skills and approximation strategies are used to convert the equivalent generalized geometric programming problem into a series of posynomial geometric programming problems that can be solved globally. Finally, we prove the convergence property and some practical application examples in optimal design domain, and arithmetic examples taken from recent literatures and GLOBALLib are carried out to validate the performance of the proposed algorithm
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