Modeling and Optimizing Routing Decisions for Travelers and On-demand Service Providers

This thesis investigates the dynamic routing decisions for individual travelers and on-demand service providers (e.g., regular taxis, Uber, Lyft, etc). For individual travelers, this thesis models and predicts route choice at two time-scales: the day-to-day and within-day. For day-to-day route choice, methodological development and empirical evidences are presented to understand the roles of learning, inertia and real-time travel information on route choices in a highly disrupted network based on data from a laboratory competitive route choice game. The learning of routing policies instead of simple paths is modeled when real-time travel information is available, where a routing policy is defined as a contingency plan that maps realized traffic conditions to path choices. Using data from a competitive laboratory experiment, prediction performance is then measured in terms of both one-step and full trajectory predictions. For within day route choice, a recursive logit model is formulated in a stochastic time-dependent (STD) network without sampling any choice sets. A decomposition algorithm is then proposed so that the model can be estimated in reasonable time. Estimation and prediction results of the proposed model are presented using a data set collected from a subnetwork of Stockholm, Sweden. Taxis and ride-sourcing vehicles play an important role in providing on-demand mobility in an urban transportation system. Unlike individual travelers, they do not have a clear destination when there\u27s no passenger on board. The optimal routing of a vacant taxi is formulated as a Markov Decision Process (MDP) problem to maximize long-term profit over the full working period. Two approaches are proposed to solve the problem. One is the model-based approach where a model of the state transitions of the environment is obtained from queuing-theory based passenger arrival and competing taxi distribution processes. An enhanced value iteration for solving the MDP problem is then proposed making use of efficient matrix operations. The other is the model-free Reinforcement Learning (RL) approach, which learns the best policy directly from observed trajectory data. Both approaches are implemented and tested in a mega city transportation network with reasonable running time, and a systematic comparison of the two approaches is also provided

Increased Expression of INHBA Is Correlated With Poor Prognosis and High Immune Infiltrating Level in Breast Cancer

Background: Inhibin, beta A (INHBA) is a member of the transforming growth factor-β superfamily and is associated with carcinogenesis and cancer progression in several types of human cancers. However, its significance in breast cancer has not been evaluated. Here, we investigated the prognostic value of INHBA and its correlation with tumor-infiltration immune cells in the microenvironment of breast cancer.Methods: In this study, we analyzed the INHBA expression profile in the Oncomine database and Tumor Immune Estimation Resource 2.0 (TIMER2.0) site. Using Breast Cancer Gene-Expression Miner (bc-GenExMiner v4.7) tool and the UALCAN cancer database, we further evaluated the correlation of INHBA expression with clinicopathological factors in breast cancer. Then, we assessed the clinical prognostic value of INHBA using Kaplan–Meier Plotter and the PrognoScan databases. The correlations between INHBA and tumor-infiltrating immune cells were investigated via TIMER2.0. In addition, correlations between INHBA expression and gene markers of immune infiltrates were analyzed by TIMER2.0 and Gene Expression Profiling Interactive Analysis 2.Results: Compared with the level in normal tissues, the INHBA mRNA expression was upregulated in different subtypes of breast cancer, and its expression was positively correlated with progesterone receptor, human epidermal growth factor receptor-2 status, and PAM50 subtypes but negatively related to age and basal-like status. The INHBA protein was also highly expressed in primary breast cancer and closely related to the pathological stage. Patients with high INHBA expression levels showed worse overall survival, relapse-free survival, and distant metastasis-free survival. Also, high INHBA expression was significantly associated with worse overall survival and relapse-free survival in positive lymph nodes. Of interest, INHBA expression was negatively correlated with infiltrating levels of activated NK cells, NKT, and CD4+ T cells but was positively correlated with tumor infiltration of CD8+ T cells, neutrophils, especially macrophages and cancer-associated fibroblasts. Moreover, INHBA expression showed strong correlations with various markers of monocytes/macrophages and cancer-associated fibroblasts.Conclusion: High INHBA expression is correlated with poor prognosis and the infiltration of immune cells in the tumor microenvironment. These findings suggest that INHBA may be involved in immune escape and can serve as a potential biomarker of prognosis and tumor-infiltrating immune cells

Identification of Ligularia Herbs Using the Complete Chloroplast Genome as a Super-Barcode

More than 30 Ligularia Cass. (Asteraceae) species have long been used in folk medicine in China. Morphological features and common DNA regions are both not ideal to identify Ligularia species. As some Ligularia species contain pyrrolizidine alkaloids, which are hazardous to human and animal health and are involved in metabolic toxification in the liver, it is important to find a better way to distinguish these species. Here, we report complete chloroplast (CP) genomes of six Ligularia species, L. intermedia, L. jaluensis, L. mongolica, L. hodgsonii, L. veitchiana, and L. fischeri, obtained through high-throughput Illumina sequencing technology. These CP genomes showed typical circular tetramerous structure and their sizes range from 151,118 to 151,253 bp. The GC content of each CP genome is 37.5%. Every CP genome contains 134 genes, including 87 protein-coding genes, 37 tRNA genes, eight rRNA genes, and two pseudogenes (ycf1 and rps19). From the mVISTA, there were no potential coding or non-coding regions to distinguish these six Ligularia species, but the maximum likelihood tree of the six Ligularia species and other related species showed that the whole CP genome can be used as a super-barcode to identify these six Ligularia species. This study provides invaluable data for species identification, allowing for future studies on phylogenetic evolution and safe medical applications of Ligularia

Seamless integration of above- and under-canopy unmanned aerial vehicle laser scanning for forest investigation

BackgroundCurrent automated forest investigation is facing a dilemma over how to achieve high tree- and plot-level completeness while maintaining a high cost and labor efficiency. This study tackles the challenge by exploring a new concept that enables an efficient fusion of aerial and terrestrial perspectives for digitizing and characterizing individual trees in forests through an Unmanned Aerial Vehicle (UAV) that flies above and under canopies in a single operation. The advantage of such concept is that the aerial perspective from the above-canopy UAV and the terrestrial perspective from the under-canopy UAV can be seamlessly integrated in one flight, thus grants the access to simultaneous high completeness, high efficiency, and low cost.ResultsIn the experiment, an approximately 0.5ha forest was covered in ca. 10min from takeoff to landing. The GNSS-IMU based positioning supports a geometric accuracy of the produced point cloud that is equivalent to that of the mobile mapping systems, which leads to a 2-4cm RMSE of the diameter at the breast height estimates, and a 4-7cm RMSE of the stem curve estimates.ConclusionsResults of the experiment suggested that the integrated flight is capable of combining the high completeness of upper canopies from the above-canopy perspective and the high completeness of stems from the terrestrial perspective. Thus, it is a solution to combine the advantages of the terrestrial static, the mobile, and the above-canopy UAV observations, which is a promising step forward to achieve a fully autonomous in situ forest inventory. Future studies should be aimed to further improve the platform positioning, and to automatize the UAV operation.Peer reviewe

Plastome Sequences Help to Resolve Deep-Level Relationships of Populus in the Family Salicaceae

Populus, a core genus of Salicaceae, plays a significant ecological role as a source of pioneer species in boreal forests. However, interspecific hybridization and high levels of morphological variation among poplars have resulted in great difficulty in classifying species for systematic and comparative evolutionary studies. Here, we present phylogenetic analyses of 24 newly sequenced Populus plastomes and 36 plastomes from GenBank, which represent seven genera of Salicaceae, in combination with a matrix of eighteen morphological characters of 40 Populus taxa to reconstruct highly supported relationships of genus Populus. Relationships among the 60 taxa of Salicaceae strongly supported two monophyletic genera: Populus and Salix. Chosenia was nested within the genus Salix, and five clades within Populus were divided. Clade I included the three taxa P. euphratica, P. pruinosa, and P. ilicifolia. Clade II contained thirteen taxa [P. adenopoda, P. alba, P. bolleana, P. davidiana, P. hopeiensis, P. nigra, P. qiongdaoensis, P. rotundifolia, P. rotundifolia var. duclouxiana, P. tremula, P. tremula × alba, P. tomentosa, and P. tomentosa (NC)]. Clade III included the ten taxa P. haoana, P. kangdingensis, P. lasiocarpa, P. pseudoglauca, P. qamdoensis, P. schneideri, P. simonii, P. szechuanica, P. szechuanica var. tibetica, and P. yunnanensis. Clade IV included P. cathayana, P. gonggaensis, P. koreana, P. laurifolia, P. trinervis, P. wilsonii, and P. xiangchengensis. The last clade comprised P. angustifolia, P. balsamifera, P. deltoides, P. deltoides × nigra, P. fremontii, P. mexicana, and P. trichocarpa. This phylogeny is also supported by morphological traits, including bark smoothness, bud size, petiole shape, leaf inflorescence, male anther length and male anther tip

International Benchmarking of the Individual Tree Detection Methods for Modeling 3-D Canopy Structure for Silviculture and Forest Ecology Using Airborne Laser Scanning

Canopy structure plays an essential role in biophysical activities in forest environments. However, quantitative descriptions of a 3-D canopy structure are extremely difficult because of the complexity and heterogeneity of forest systems. Airborne laser scanning (ALS) provides an opportunity to automatically measure a 3-D canopy structure in large areas. Compared with other point cloud technologies such as the image-based Structure from Motion, the power of ALS lies in its ability to penetrate canopies and depict subordinate trees. However, such capabilities have been poorly explored so far. In this paper, the potential of ALS-based approaches in depicting a 3-D canopy structure is explored in detail through an international benchmarking of five recently developed ALS-based individual tree detection (ITD) methods. For the first time, the results of the ITD methods are evaluated for each of four crown classes, i.e., dominant, codominant, intermediate, and suppressed trees, which provides insight toward understanding the current status of depicting a 3-D canopy structure using ITD methods, particularly with respect to their performances, potential, and challenges. This benchmarking study revealed that the canopy structure plays a considerable role in the detection accuracy of ITD methods, and its influence is even greater than that of the tree species as well as the species composition in a stand. The study also reveals the importance of utilizing the point cloud data for the detection of intermediate and suppressed trees. Different from what has been reported in previous studies, point density was found to be a highly influential factor in the performance of the methods that use point cloud data. Greater efforts should be invested in the point-based or hybrid ITD approaches to model the 3-D canopy structure and to further explore the potential of high-density and multiwavelengths ALS data

Seamless integration of above- and under-canopy unmanned aerial vehicle laser scanning for forest investigation

BackgroundCurrent automated forest investigation is facing a dilemma over how to achieve high tree- and plot-level completeness while maintaining a high cost and labor efficiency. This study tackles the challenge by exploring a new concept that enables an efficient fusion of aerial and terrestrial perspectives for digitizing and characterizing individual trees in forests through an Unmanned Aerial Vehicle (UAV) that flies above and under canopies in a single operation. The advantage of such concept is that the aerial perspective from the above-canopy UAV and the terrestrial perspective from the under-canopy UAV can be seamlessly integrated in one flight, thus grants the access to simultaneous high completeness, high efficiency, and low cost.ResultsIn the experiment, an approximately 0.5ha forest was covered in ca. 10min from takeoff to landing. The GNSS-IMU based positioning supports a geometric accuracy of the produced point cloud that is equivalent to that of the mobile mapping systems, which leads to a 2-4cm RMSE of the diameter at the breast height estimates, and a 4-7cm RMSE of the stem curve estimates.ConclusionsResults of the experiment suggested that the integrated flight is capable of combining the high completeness of upper canopies from the above-canopy perspective and the high completeness of stems from the terrestrial perspective. Thus, it is a solution to combine the advantages of the terrestrial static, the mobile, and the above-canopy UAV observations, which is a promising step forward to achieve a fully autonomous in situ forest inventory. Future studies should be aimed to further improve the platform positioning, and to automatize the UAV operation

Airborne laser scanning outperforms the alternative 3D techniques in capturing variation in tree height and forest density in southern boreal forests.

ArticleBaltic Forestry. 24(2): 268-277. (2018)journal articl

Airborne Laser Scanning Outperforms the Alternative 3D Techniques in Capturing Variation in Tree Height and Forest Density in Southern Boreal Forests

The objective of this study is to better understand the relationship between forest structure and point cloud features generated from certain airborne and space borne sensors. Point cloud features derived from airborne laser scanning (ALS), aerial imagery (AI), WorldView-2 imagery (WV2), TerraSAR-X, and Tandem-X (TDX) data were classified as features characterizing forest height and density as well as variation in tree height. Correlations between these features and field-measured attributes describing forest height, density and tree height variation were investigated at plot scale. From the field-measured attributes, basal area (G) and the number of trees per unit area (N) were used as forest density indicators whereas maximum tree height (H-max) and standard deviation in tree height (H-std) were used as indicators for forest height and tree height variation, respectively. In the analyses, field observations from 91 sample plots (32 m x 32 m) located in southern Finland were used. Even though ALS was found to be the most accurate data source in characterizing forest structure, AI, WV2, and TDX were also capable of characterizing forest height at plot scale with correlation coefficients stronger than 0.85. However, ALS was the only data source capable of providing separate features for characterizing also the variation in tree height and forest density. Features related to forest height, generated from the other data sources besides ALS, also provided strongest correlation with the forest density attributes and variation in tree height, in addition to H-max. Due to these more diverse characterization capabilities, forest structural attributes can be predicted more accurately by using ALS, also in the areas where the relation between the attributes of interest is not solely dependent on forest height, compared to the other investigated 3D remote sensing data sources.Peer reviewe