Statistical Properties of a Convoluted Beta-Weibull Distribution

A new class of distributions recently developed involves the logit of the beta distribution. Among this class of distributions are the beta-normal (Eugene et.al. (2002)); beta-Gumbel (Nadarajah and Kotz (2004)); beta-exponential (Nadarajah and Kotz (2006)); beta-Weibull (Famoye et al. (2005)); beta-Rayleigh (Akinsete and Lowe (2008)); beta-Laplace (Kozubowski and Nadarajah (2008)); and beta-Pareto (Akinsete et al. (2008)), among a few others. Many useful statistical properties arising from these distributions and their applications to real life data have been discussed in the literature. One approach by which a new statistical distribution is generated is by the transformation of random variables having known distribution function(s). The focus of this work is to investigate the statistical properties of the convoluted beta-Weibull distribution, defined and extensively studied by Famoye et al. (2005). That is, if X is a random variable having the beta-Weibull distribution with parameters a1, B1, c1, y1 i.e. X=BW(a1, B1, c1 and y1) and Y has a beta-Weibull distribution expressed as Y=BW(a2, B2, c2, y2) what then is the distribution of the convolution of X and Y. That is, the distribution of the random variable Z=X+Y. We obtain the probability density function (pdf) and the cumulative distribution function (cdf) of the convoluted distribution. Various statistical properties of this distribution are obtained, including, for example, moment, moment and characteristic generating functions, hazard function, and the entropy. We propose the method of Maximum Likelihood Estimation (MLE) for estimating the parameters of the distribution. The open-source software R is used extensively in implementing our results

External Economic Costs of Intelligent Urban Transportation Systems: A Method to Evaluate the Externalities of Comparative Technology Adoption Pathways in the Urban Mobility Service sector

By 2050, urban mobility demands will increase to 2.6 times the current level, even faster than the urban population growth. Current urban transportation plans fail to address these rapidly increasing urban mobility demands. Inefficient urban transportation generates great economic losses in traffic congestion, air pollution and climate change. The current urban transportation pressure and emerging technology-driven trends have revolutionized how industry players respond to changing consumer behavior, develop partnerships, and drive transformational changes. A transition (P2S) from current product-based competition to a marketplace focused on mobility services is expected. Electric vehicles, automated driving systems and mobility-sharing platforms are introduced to provide mobility services by market-agents in the P2S transition. The adoption of these technologies has proven to be beneficial in simulations. In reality, externalities occur when introducing disruptive technologies into a marketplace with the absence of instrumental institutions (non-market agents). However, all agents fail to evaluate the economic impacts of different technology adoption pathways at the mass-adoption scale. The method proposed in this research contains: (1) a resource-demand view framework to capture multiple technology adoption pathways in the P2S transition (2) scenario designs that integrate electric vehicle technology, automated driving systems, and mobility sharing platforms in one or several combinations (3) a set of economic externality models to evaluate the costs of traffic congestion, human health impact, and climate change resulting from each variation. This dissertation is an informative comparative study that demonstrates the externalities (social economic impacts) of different sets of technology adoptions in urban mobility. Regulators can utilize the method while funding research and designing regulations for disruptive automotive technologies. The method also provides a platform for market-agents to quantify the economic impact of new product designs in the mobility marketplace

Which Framework is Suitable for Online 3D Multi-Object Tracking for Autonomous Driving with Automotive 4D Imaging Radar?

Online 3D multi-object tracking (MOT) has recently received significant research interests due to the expanding demand of 3D perception in advanced driver assistance systems (ADAS) and autonomous driving (AD). Among the existing 3D MOT frameworks for ADAS and AD, conventional point object tracking (POT) framework using the tracking-by-detection (TBD) strategy has been well studied and accepted for LiDAR and 4D imaging radar point clouds. In contrast, extended object tracking (EOT), another important framework which accepts the joint-detection-and-tracking (JDT) strategy, has rarely been explored for online 3D MOT applications. This paper provides the first systematical investigation of the EOT framework for online 3D MOT in real-world ADAS and AD scenarios. Specifically, the widely accepted TBD-POT framework, the recently investigated JDT-EOT framework, and our proposed TBD-EOT framework are compared via extensive evaluations on two open source 4D imaging radar datasets: View-of-Delft and TJ4DRadSet. Experiment results demonstrate that the conventional TBD-POT framework remains preferable for online 3D MOT with high tracking performance and low computational complexity, while the proposed TBD-EOT framework has the potential to outperform it in certain situations. However, the results also show that the JDT-EOT framework encounters multiple problems and performs inadequately in evaluation scenarios. After analyzing the causes of these phenomena based on various evaluation metrics and visualizations, we provide possible guidelines to improve the performance of these MOT frameworks on real-world data. These provide the first benchmark and important insights for the future development of 4D imaging radar-based online 3D MOT.Comment: 8 pages, 5 figures, submitted to the 2024 IEEE International Conference on Robotics and Automation (ICRA2024

Co-cultivation of Trichoderma asperellum GDFS1009 and Bacillus amyloliquefaciens 1841 Causes Differential Gene Expression and Improvement in the Wheat Growth and Biocontrol Activity

In an effort to balance the demands of plant growth promoting and biological control agents in a single product, the technology on the co-cultivation of two microbes, Trichoderma asperellum GDFS1009 and Bacillus amyloliquefaciens 1841 has been developed and demonstrated its effectiveness in synergistic interactions and its impact on the plant growth and biocontrol potential. In this study, optimization of T. asperellum and B. amyloliquefaciens growth in a single medium was carried out using response surface methodology (RSM). The optimal medium for enhanced growth was estimated as 2% yeast extract, 2% molasses and 2% corn gluten meal. T. asperellum evolved the complicated molecular mechanisms in the co-culture by the induction of BLR-1/BLR-2, VELVET, and NADPH oxidases genes. In performance with these genes, conserved signaling pathways, such as heterotrimeric G proteins and mitogen-activated protein kinases (MAPKs) had also involved in this molecular orchestration. The co-cultivation induced the expression of T. asperellum genes related to secondary metabolism, mycoparasitism, antioxidants and plant growth. On the other hand, the competition during co-cultivation induced the production of new compounds that are not detected in axenic cultures. In addition, the co-culture significantly enhanced the plant growth and protection against Fusarium graminearum. The present study demonstrated the potential of co-cultivation technology could be a used to grow the T. asperellum GDFS1009 and B. amyloliquefaciens 1841 synergistically to improve the production of mycoparasitism related enzymes, secondary metabolites, and plant growth promoting compounds to significantly enhance the plant growth and protection against plant pathogens

Preparation and Characterization of Gummies Loaded with Melatonin and Lycium barbarum L.

In order to expand the application of melatonin in gel food, convenient gummies loaded with melatonin and Lycium barbarum L. were developed in this study. The comprehensive effects of gelatin dose, Lycium barbarum L. powder level and drying time on the properties of melatonin gummies were investigated by color difference analysis, texture analysis, low field NMR analysis and sensory evaluation. The results showed that the gummies containing with 0.4% Lycium barbarum L. powder, 18% gelatin, 5% carrageenan, 17.5% sorbitol, 17.5% erythritol and drying for 18 h were elastic and palatable with smooth surface. The gummies had moisture content less than 20% and melatonin retention rate of 92.0%~97.7%, and high sensory evaluation with potential practical application

Multiplex immunofluorescence-guided laser capture microdissection for spatial transcriptomics of metastatic melanoma tissues.

We describe a pipeline for optimized and streamlined multiplexed immunofluorescence-guided laser capture microdissection allowing the harvest of individual cells based on their phenotype and tissue localization for transcriptomic analysis with next-generation RNA sequencing. Here, we analyze transcriptomes of CD3+ T cells, CD14+ monocytes/macrophages, and melanoma cells in non-dissociated metastatic melanoma tissue. While this protocol is described for melanoma tissues, we successfully applied it to human tonsil, skin, and breast cancer tissues as well as mouse lung tissues. For complete details on the use and execution of this protocol, please refer to Martinek et al. (2022)