Development of emergency response systems by intelligent and integrated approaches for marine oil spill accidents

Oil products play a pervasive role in modern society as one of the dominant energy fuel sources. Marine activities related to oil extraction and transportation play a vital role in resource supply. However, marine oil spills occur due to such human activities or harsh environmental factors. The emergency accidents of spills cause negative impacts on the marine environment, human health, and economic loss. The responses to marine oil spills, especially large-scale spills, are relatively challenging and inefficient due to changing environmental conditions, limited response resources, various unknown or uncertain factors and complex resource allocation processes. The development of previous research mainly focused on single process simulation, prediction, or optimization (e.g., oil trajectory, weathering, or cleanup optimization). There is still a lack of research on comprehensive and integrated emergency responses considering multiple types of simulations, types of resource allocations, stages of accident occurrence to response, and criteria for system optimizations. Optimization algorithms are an important part of system optimization and decision-making. Their performance directly affacts the quality of emergency response systems and operations. Thus, how to improve efficiency of emergency response systems becomes urgent and essential for marine oil spill management. The power and potential of integrating intelligent-based modeling of dynamic processes and system optimization have been recognized to better support oil spill responders with more efficient response decisions and planning tools. Meanwhile, response decision-making combined with human factor analysis can help quantitatively evaluate the impacts of multiple causal factors on the overall processes and operational performance after an accident. To address the challenges and gaps, this dissertation research focused on the development and improvement of new emergency response systems and their applications for marine oil spill response in the following aspects: 1) Realization of coupling dynamic simulation and system optimization for marine oil spill responses - The developed Simulation-Based Multi-Agent Particle Swarm Optimization (SA-PSO) modeling investigated the capacity of agent-based modeling on dynamic simulation of spill fate and response, particle swarm optimization on response allocation with minimal time and multi-agent system on information sharing. 2) Investigation of multi-type resource allocation under a complex simulation condition and improvement of optimization performance - The improved emergency response system was achieved by dynamic resource transportation, oil weathering and response simulations and resource allocation optimization. The enhanced particle swarm optimization (ME-PSO) algorithm performed outstanding convergence performance and low computation cost characteristics integrating multi-agent theory (MA) and evolutionary population dynamics (EPD). 3) Analysis and evaluation of influencing factors of multiple stages of spill accidents based on human factors/errors and multi-criteria decision making - The developed human factors analysis and classification system for marine oil spill accidents (HFACS-OS) framework qualitatively evaluated the influence of various factors and errors associated with the multiple operational stages considered for oil spill preparedness and response (e.g., oil spill occurrence, spill monitoring, decision making/contingency planning, and spill response). The framework was further coupled with quantitative data analysis by Fuzzy-based Technique for Order Preference by Similarity to Idea Solution (Fuzzy-TOPSIS) to enhance decision-making during response operations under multiple criteria. 4) Development of a multi-criteria emergency response system with the enhanced optimization algorithm, multi-mode resource transportation and allocation and a more complex and realistic simulation modelling - The developed multi-criteria emergency response system (MC-ERS) system integrated dynamic process simulations and weighted multi-criteria system optimization. Total response time, response cost and environmental impacts were regarded as multiple optimization goals. An improved weighted sum optimization function was developed to unify the scaling and proportion of different goals. A comparative PSO was also developed with various algorithm-improving methods and the best-performing inertia weight function. The proposed emergency response approaches in studies were examined by oil spill case studies related to the North Atlantic Ocean and Canada circumstances to analyze the modelling performance and evaluate their practicality and applicability. The developed optimization algorithms were tested by benchmarked functions, other optimization algorithms, and an oil spill case. The developed emergency response systems and the contained simulation and optimization algorithms showed the strong capability for decision-making and emergency responses by recommending optimal resource management or evaluations of essential factors. This research was expected to provide time-efficient, and cost-saving emergency response management approaches for handling and managing marine oil spills. The research also improved our knowledge of the significance of human factors/errors to oil spill accidents and response operations and provided improved support tools for decision making. The dissertation research helped fill some important gaps in emergency response research and management practice, especially in marine oil spill response, through an innovative integration of dynamic simulation, resource optimization, human factor analysis, and artificial intelligence methods. The research outcomes can also provide methodological support and valuable references for other fields that require timely and effective decisions, system optimizations, process controls, planning and designs under complicated conditions, uncertainties, and interactions

Free Vibration Analysis for Shells of Revolution Using an Exact Dynamic Stiffness Method

An exact generalised formulation for the free vibration of shells of revolution with general shaped meridians and arbitrary boundary conditions is introduced. Starting from the basic shell theories, the vibration governing equations are obtained in the Hamilton form, from which dynamic stiffness is computed using the ordinary differential equations solver COLSYS. Natural frequencies and modes are determined by employing the Wittrick-Williams (W-W) algorithm in conjunction with the recursive Newton’s method, thus expanding the applications of the abovementioned techniques from one-dimensional skeletal structures to two-dimensional shells of revolution. A solution for solving the number of clamped-end frequencies J0 in the W-W algorithm is presented for both uniform and nonuniform shell segment members. Based on these theories, a FORTRAN program is written. Numerical examples on circular cylindrical shells, hyperboloidal cooling tower shells, and spherical shells are given, and error analysis is performed. The convergence of the proposed method on J0 is verified, and comparisons with frequencies from existing literature show that the dynamic stiffness method is robust, reliable, and accurate

HyperStyle3D: Text-Guided 3D Portrait Stylization via Hypernetworks

Portrait stylization is a long-standing task enabling extensive applications. Although 2D-based methods have made great progress in recent years, real-world applications such as metaverse and games often demand 3D content. On the other hand, the requirement of 3D data, which is costly to acquire, significantly impedes the development of 3D portrait stylization methods. In this paper, inspired by the success of 3D-aware GANs that bridge 2D and 3D domains with 3D fields as the intermediate representation for rendering 2D images, we propose a novel method, dubbed HyperStyle3D, based on 3D-aware GANs for 3D portrait stylization. At the core of our method is a hyper-network learned to manipulate the parameters of the generator in a single forward pass. It not only offers a strong capacity to handle multiple styles with a single model, but also enables flexible fine-grained stylization that affects only texture, shape, or local part of the portrait. While the use of 3D-aware GANs bypasses the requirement of 3D data, we further alleviate the necessity of style images with the CLIP model being the stylization guidance. We conduct an extensive set of experiments across the style, attribute, and shape, and meanwhile, measure the 3D consistency. These experiments demonstrate the superior capability of our HyperStyle3D model in rendering 3D-consistent images in diverse styles, deforming the face shape, and editing various attributes

Multi-dark-state resonances in cold multi-Zeeman-sublevel atoms

We present our experimental and theoretical studies of multi-dark-state resonances (MDSRs) generated in a unique cold rubidium atomic system with only one coupling laser beam. Such MDSRs are caused by different transition strengths of the strong coupling beam connecting different Zeeman sublevels. Controlling the transparency windows in such electromagnetically induced transparency system can have potential applications in multi-wavelength optical communication and quantum information processing.Comment: 11pages, 4figure

Role and therapeutic potential of DEAD-box RNA helicase family in colorectal cancer

Colorectal cancer (CRC) is the third most commonly diagnosed and the second cancer-related death worldwide, leading to more than 0.9 million deaths every year. Unfortunately, this disease is changing rapidly to a younger age, and in a more advanced stage when diagnosed. The DEAD-box RNA helicase proteins are the largest family of RNA helicases so far. They regulate almost every aspect of RNA physiological processes, including RNA transcription, editing, splicing and transport. Aberrant expression and critical roles of the DEAD-box RNA helicase proteins have been found in CRC. In this review, we first summarize the protein structure, cellular distribution, and diverse biological functions of DEAD-box RNA helicases. Then, we discuss the distinct roles of DEAD-box RNA helicase family in CRC and describe the cellular mechanism of actions based on recent studies, with an aim to provide future strategies for the treatment of CRC

TiEV: The Tongji Intelligent Electric Vehicle in the Intelligent Vehicle Future Challenge of China

TiEV is an autonomous driving platform implemented by Tongji University of China. The vehicle is drive-by-wire and is fully powered by electricity. We devised the software system of TiEV from scratch, which is capable of driving the vehicle autonomously in urban paths as well as on fast express roads. We describe our whole system, especially novel modules of probabilistic perception fusion, incremental mapping, the 1st and the 2nd planning and the overall safety concern. TiEV finished 2016 and 2017 Intelligent Vehicle Future Challenge of China held at Changshu. We show our experiences on the development of autonomous vehicles and future trends

Efficacy of sorafenib on metastatic renal cell carcinoma in Asian patients: Results from a multicenter study

<p>Abstract</p> <p>Background</p> <p>The effects of sorafenib in the treatment of advanced renal cell carcinoma (RCC) have been confirmed in an international collaborative phase III trial. This study aims to confirm similar efficacy and treatment-induced toxicities of sorafenib in the treatment of metastatic RCC in ethnic Chinese patients.</p> <p>Methods</p> <p>Ninety-eight consecutive and non-selected patients with pathologically confirmed metastatic RCC were treated according to an institutional treatment protocol. All patients were treated with 400 mg of sorafenib orally twice daily on a continuous basis until disease progression or intolerance to treatment occurred. Dose reduction to 400 mg once daily was required if grade 3 or 4 toxicities occurred. All patients except for 7 received nephrectomy in the course of their disease. All patients were assessed for tumor response, progression-free survival (PFS), overall survival (OS), and treatment-induced toxicities.</p> <p>Results</p> <p>The median follow-up time was 76 weeks (range 2–296 weeks) for the entire group of patients. Radiologically confirmed complete response (CR), partial response (PR), stable disease (SD) of more than 4 months, and disease progression as best objective responses were observed in 1 (1%), 23 (23.5%), 62 (63.3%), and 12 (12.2%) patients, respectively. The tumor control rate (CR+PR+SD of >4 months) was 87.8%. The 1-year estimated PFS and OS were 58.4% and 64.6%, respectively. The median progression-free survival (PFS) time was 60 weeks (95% CI 41–79); and the median overall survival (OS) time was not reached with a follow-up of 76 weeks. Reduction of sorafenib dose was required in 26 patients who developed grade 3 or 4 treatment-cause adverse-effects. An additional 9 patients discontinued sorafenib treatment due to severe adverse-effects. No grade 5 toxicity occurred.</p> <p>Multivariate analysis revealed that independent predictive factors for tumor response to sorafenib treatment included ECOG status, presence of lymph node metastasis, and nephrectomy prior to the development of metastasis.</p> <p>Conclusion</p> <p>Sorafenib produced an 87.8% disease control rate for metastatic renal cell carcinoma in Chinese patients, with acceptable rates of toxicity. The medication dosed at 400 mg twice daily is both efficacious and safe in the treatment of metastatic renal cell carcinoma in Chinese patients.</p