132571 research outputs found
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Large-scale dose evaluation of deep learning organ contours in head-and-neck radiotherapy by leveraging existing plans
No full textBackground and purpose: Retrospective dose evaluation for organ-at-risk auto-contours has previously used small cohorts due to additional manual effort required for treatment planning on auto-contours. We aimed to do this at large scale, by a) proposing and assessing an automated plan optimization workflow that used existing clinical plan parameters and b) using it for head-and-neck auto-contour dose evaluation. Materials and methods: Our automated workflow emulated our clinic's treatment planning protocol and reused existing clinical plan optimization parameters. This workflow recreated the original clinical plan (POG) with manual contours (PMC) and evaluated the dose effect (POG-PMC) on 70 photon and 30 proton plans of head-and-neck patients. As a use-case, the same workflow (and parameters) created a plan using auto-contours (PAC) of eight head-and-neck organs-at-risk from a commercial tool and evaluated their dose effect (PMC-PAC). Results: For plan recreation (POG-PMC), our workflow had a median impact of 1.0% and 1.5% across dose metrics of auto-contours, for photon and proton respectively. Computer time of automated planning was 25% (photon) and 42% (proton) of manual planning time. For auto-contour evaluation (PMC-PAC), we noticed an impact of 2.0% and 2.6% for photon and proton radiotherapy. All evaluations had a median ΔNTCP (Normal Tissue Complication Probability) less than 0.3%. Conclusions: The plan replication capability of our automated program provides a blueprint for other clinics to perform auto-contour dose evaluation with large patient cohorts. Finally, despite geometric differences, auto-contours had a minimal median dose impact, hence inspiring confidence in their utility and facilitating their clinical adoption.Computer Graphics and Visualisatio
A conceptual framework for automation disengagements
No full textA better understanding of automation disengagements can lead to improved safety and efficiency of automated systems. This study investigates the factors contributing to automation disengagements initiated by human operators and the automation itself by analyzing semi-structured interviews with 103 users of Tesla’s Autopilot and FSD Beta. The factors leading to automation disengagements are represented by categories. In total, we identified five main categories, and thirty-five subcategories. The main categories include human operator states (5), human operator’s perception of the automation (17), human operator’s perception of other humans (3), the automation’s perception of the human operator (3), and the automation incapability in the environment (7). Human operators disengaged the automation when they anticipated failure, observed unnatural or unwanted automation behavior (e.g., erratic steering, running red lights), or believed the automation is not capable to operate safely in certain environments (e.g., inclement weather, non-standard roads). Negative experiences of human operators, such as frustration, unsafe feelings, and distrust represent some of the adverse human operate states leading to automation disengagements initiated by human operators. The automation, in turn, monitored human operators and disengaged itself if it detected insufficient vigilance or speed rule violations by human operators. Moreover, human operators can be influenced by the reactions of passengers and other road users, leading them to disengage the automation if they sensed discomfort, anger, or embarrassment due to the automation’s actions. The results of the analysis are synthesized into a conceptual framework for automation disengagements, borrowing ideas from the human factor's literature and control theory. This research offers insights into the factors contributing to automation disengagements, and highlights not only the concerns of human operators but also the social aspects of this phenomenon. The findings provide information on potential edge cases of automated vehicle technology, which may help to enhance the safety and efficiency of such systems.Transport and Plannin
The Estimation of Acoustic Parameters and Representations based on Room Impulse Responses
No full textWe are surrounded by all kinds of sounds at all times. What we hear varies with the physical environment and our position. Room impulse responses (RIRs) characterize the effect of the environment on a sound produced by a source. A first goal of this dissertation is to analyze RIRs and investigate how to extract environmental information from RIRs. Immersive digital environments, such as virtual reality (VR) and augmented reality (AR), play an increasingly important role in society. Spatial audio, aiming to give listeners a 3D audio experience, is vital to immersive digital environments. Omnidirectional RIRs do not provide explicit spatial information for room acoustics applications. As a result, the description and reproduction of the sound field is of great importance for spatial audio. Specifically, we consider higher order ambisonics, which is the prevalent method to represent the sound field around a listener. The synthesis of ambisonics signals is a second goal of this dissertation....Signal Processing System
Structure Guided Directed Evolution of Enzymes
No full textOur ability to tailor enzymatic properties is a critical factor for biocatalyst application in the industrial sector. Although many wild-type enzymes have been found capable of promiscuously catalysing desired anthropogenic reactions, their activity and selectivity for non-natural transformations is often poor. Consequently, it is crucial to optimise enzymes such that they can be effectively integrated into industrial processes. Notable added advantages in this context are that enzymes are considered 'green' catalysts - enhancing the perceived value of products in today's environmentally-conscious society – and that biocatalysts can carry out intricate chemistries with exceptional regio- and stereoselectivity, complementing traditional organic synthesis.BT/Biocatalysi
Exploring the challenges faced by Dutch truck drivers in the era of technological advancement
No full textIntroduction: Despite their important role in the economy, truck drivers face several challenges, including adapting to advancing technology. The current study investigated the occupational experiences of Dutch truck drivers to detect common patterns.Methods: A questionnaire was distributed to professional drivers in order to collect data on public image, traffic safety, work pressure, transport crime, driver shortage, and sector improvements.Results: The findings based on 3,708 respondents revealed a general dissatisfaction with the image of the industry and reluctance to recommend the profession. A factor analysis of the questionnaire items identified two primary factors: ‘Work Pressure’, more common among national drivers, and ‘Safety & Security Concerns’, more common among international drivers. A ChatGPT-assisted analysis of textbox comments indicated that vehicle technology received mixed feedback, with praise for safety and fuel-efficiency improvements, but concerns about reliability and intrusiveness.Discussion: In conclusion, Dutch professional truck drivers indicate a need for industry improvements. While the work pressure for truck drivers in general may not be high relative to certain other occupational groups, truck drivers appear to face a deficit of support and respect.Human-Robot InteractionMedical Instruments & Bio-Inspired Technolog
The direct effect of CO2 rise on the plant ionome: Implications for Exacerbating Global Malnutrition
No full textMalnutrition is worsening, affecting every country and over 3 billion people. There is evidence that rising CO2 levels will not only indirectly increase malnutrition through climate change effects, but also directly through a downshift in the plant ionome, reducing nutritional quality and increasing hidden hunger. Attempts to calculate the human health impact have been conducted with limited statistical power on a small group of nutrients. The impact on different age-sex groups, countries, and nutrients is still largely unknown. This research aims to fill this gap, creating a meta-analysis of the most data (5,809 entries), crops (43), and elements (31 plus phytate) of any study to date, resolving a methodological gap for disharmonious data and applying this to the GENuS model of global nutritional supply in 2011 for eight nutrients (calcium, copper, iron, magnesium, phosphorus, potassium, protein, and zinc) to see which countries will be able to provide enough nutrients for their citizens in a 550 ppm world compared to at 350 ppm.Bootstrapping reveals a distinct 5% to 12% systemic downshift in the plant ionome. Both C3 and C4 plants respond, disproving the hypothesis that C4 plants are mostly unaffected by CO2 rise and supporting the idea that the CO2 saturation point is not directly linked to mineral uptake. Elements have a differential response, suggesting that the carbon dilution theory is an inappropriate explanation. Zinc, protein, and iron have the largest decreases, and zinc in chickpeas decreases the most (40%) of all groups. Grains (wheat and rice) and soybeans are the hardest hit crops, decreasing in nutritional value up to 12%. The total nutrient supply decreases by 2.3% to 6.4%, increasing the malnourishment and obesity double burden. Countries will no longer provide enough nutrients from food solely due to changes in the plant ionome, impacting every country. Half of the world will develop new deficiencies. The strongest predictor of resiliency to nutritional changes from CO2 rise is diet diversity. Exacerbating global inequality, the impact will be particularly pronounced in African and Asian countries, and among women aged 25-29 compared to men of the same age group and children aged 0-4 years. Changing plant stoichiometry will have dramatic global implications for hidden hunger, worsening or introducing deficiencies, especially in iron, phosphorus, potassium, and zinc.Code and dataset available upon request. They will be uploaded publicly once the thesis has been submitted for publication.Industrial Ecolog
Additive-Free Near-Intrinsic Narrow Band Gap Perovskites via Sequential Thermal Evaporation: for Photovoltaic Applications
No full textTin/lead (Sn/Pb) iodide perovskites (PVKs) have emerged as promising absorber layer materials for high-efficiency tandem solar cells due to their low cost, high light absorption coefficients, and narrow band gaps. However, current solvent-based synthesis techniques offer poor scalability, in turn hindering commercialization.This study introduces sequential thermal evaporation (STE) as a scalable method for producing narrow band gap Sn/Pb iodide PVK absorber layers for application in solar cells. The produced thin films show low doping densities, charge carrier mobilities close to 100 cm2/Vs, and charge carrier lifetimes of over 2 μs. Contrary to the established convention in solvent-based synthesis, no additives were required.An alloy of precursors (PbSnI4) was used in the deposition, lowering the number of requiredsources and increasing the production rate. Optimal annealing temperatures for FAPb0.5Sn0.5I3 and Cs0.05FA0.95Pb0.5Sn0.5I3 produced via STE were determined at 200 ◦C, showing significant improvements in charge carrier mobilities and lifetimes compared to lower annealing temperatures. The drastic increase in performance was ascribed to a recrystallization mechanism. Contrary to spin coating-based research, the introduction of cesium into the PVK structure led to reduced charge carrier mobility and lifetime. The underlying mechanism remains unclear. Addition of tin(II)fluoride (SnF2) led to reduced charge carrier mobilities and lifetimes, with slight improvement in morphology. However, its direct effects were uncertain, questioning its necessity in vacuum deposition methods for Sn-based PVK films. This works demonstrates the significant potential of STE for the production of near-intrinsic high-performance Sn/Pb iodide PVKs for solar cell applications.Chemical Engineerin
How Do Developers Influence the Transaction Costs of China’s Prefabricated Housing Development Process?: An Investigation Through the Bayesian Belief Network Approach
No full textThe implementation of prefabricated housing (PH) has become prevalent in China recently due to its advantages in enhancing production and energy-saving efficiency within the construction system. However, stakeholders may not always fully realize the benefits of adopting PH due to the emergence of transaction costs (TCs) in the development process of such projects. This study investigated the strategies for developers to make rational choices for minimizing the TCs of the PH project considering their own attributes and external constraints. A Bayesian Belief Network model was applied as the analytical method, based on surveys conducted in China. A single sensitivity analysis indicated that developers influence the TCs of PH through the following three most impactful factors: prefabrication rate, PH experience, and contract payment method. Integrated strategies are recommended for developers in various situations based on a multiple sensitivity analysis. Developers facing challenges due to high prefabrication rates are advised to reduce the risks by procuring highly qualified general contractors and adopting unit-price contracts. For developers with limited PH experience, adopting the Engineering–Procurement–Construction procurement method is the most efficient way to reduce their TCs in the context of China’s PH market. This study contributes to the current body of knowledge concerning the effect of traders’ attributes and choices on TCs, expanding the application of TC theory and fulfilling the study on the determinants of TCs in construction management.Design & Construction Managemen
Feyenoord City leert ons het belang van lerende gebiedsontwikkeling
No full textFeyenoord City in Rotterdam is een grote gebiedsontwikkeling die zonder nieuw stadion van de gelijknamige voetbalclub de belangrijkste aanjager verloor. Had dit anders gekund? Wat is uit alle lessen van Feyenoord City de belangrijkste voor andere complexe gebiedsontwikkelingen? Onderzoekers van Arcadis wijzen op het belang van leren in gebiedsontwikkeling.Urban Development Managemen
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