Digital user's decision journey

The landscape of the Internet is continually evolving. This creates huge opportunities for different industries to optimize vital channels online, resulting in various-forms of new Internet services. As a result, digital users are interacting with many digital systems and they are exhibiting dynamic behaviors. Their shopping behaviors are drastically different today than it used to be, with offline and online shopping interacting with each other. They have many channels to access online media but their consumption patterns on different channels are quite different. They do philanthropy online to help others but their heterogeneous motivations and different fundraising campaigns leads to distinct path-to-contribution. Understanding the digital user’s decision making process behind their dynamic behaviors is critical as they interact with various digital systems for the firms to improve user experience and improve their bottom line. In this thesis, I study digital users’ decision journeys and the corresponding digital technology firms’ strategies using inter-disciplinary approaches that combine econometrics, economic structural modeling and machine learning. The uncovered decision journey not only offer empirical managerial insights but also provide guideline for introducing intervention to better serve digital users

AST-GIN: Attribute-Augmented Spatial-Temporal Graph Informer Network for Electric Vehicle Charging Station Availability Forecasting

Electric Vehicle (EV) charging demand and charging station availability forecasting is one of the challenges in the intelligent transportation system. With the accurate EV station situation prediction, suitable charging behaviors could be scheduled in advance to relieve range anxiety. Many existing deep learning methods are proposed to address this issue, however, due to the complex road network structure and comprehensive external factors, such as point of interests (POIs) and weather effects, many commonly used algorithms could just extract the historical usage information without considering comprehensive influence of external factors. To enhance the prediction accuracy and interpretability, the Attribute-Augmented Spatial-Temporal Graph Informer (AST-GIN) structure is proposed in this study by combining the Graph Convolutional Network (GCN) layer and the Informer layer to extract both external and internal spatial-temporal dependence of relevant transportation data. And the external factors are modeled as dynamic attributes by the attribute-augmented encoder for training. AST-GIN model is tested on the data collected in Dundee City and experimental results show the effectiveness of our model considering external factors influence over various horizon settings compared with other baselines.Comment: 10 pages; 17 figures; Under review for IEEE Transaction on Vehicular Technolog

The Evolution of the Galaxy Stellar Mass Function at z= 4-8: A Steepening Low-mass-end Slope with Increasing Redshift

We present galaxy stellar mass functions (GSMFs) at $z=$ 4-8 from a rest-frame ultraviolet (UV) selected sample of $\sim$4500 galaxies, found via photometric redshifts over an area of $\sim$280 arcmin$^2$ in the CANDELS/GOODS fields and the Hubble Ultra Deep Field. The deepest Spitzer/IRAC data yet-to-date and the relatively large volume allow us to place a better constraint at both the low- and high-mass ends of the GSMFs compared to previous space-based studies from pre-CANDELS observations. Supplemented by a stacking analysis, we find a linear correlation between the rest-frame UV absolute magnitude at 1500 \AA\ ($M_{\rm UV}$) and logarithmic stellar mass ($\log M_*$) that holds for galaxies with $\log(M_*/M_{\odot}) \lesssim 10$. We use simulations to validate our method of measuring the slope of the $\log M_*$-$M_{\rm UV}$ relation, finding that the bias is minimized with a hybrid technique combining photometry of individual bright galaxies with stacked photometry for faint galaxies. The resultant measured slopes do not significantly evolve over $z=$ 4-8, while the normalization of the trend exhibits a weak evolution toward lower masses at higher redshift. We combine the $\log M_*$-$M_{\rm UV}$ distribution with observed rest-frame UV luminosity functions at each redshift to derive the GSMFs, finding that the low-mass-end slope becomes steeper with increasing redshift from $\alpha=-1.55^{+0.08}_{-0.07}$ at $z=4$ to $\alpha=-2.25^{+0.72}_{-0.35}$ at $z=8$. The inferred stellar mass density, when integrated over $M_*=10^8$-$10^{13} M_{\odot}$, increases by a factor of $10^{+30}_{-2}$ between $z=7$ and $z=4$ and is in good agreement with the time integral of the cosmic star formation rate density.Comment: 27 pages, 17 figures, ApJ, in pres

Construction and optimization of ecological security pattern based on landscape ecological risk assessment in the affected area of the Lower Yellow River

In the context of urban expansion and climate change, the world is under pressure from multiple ecological risks. Key ecological protection areas play a pivotal role in preserving ecological stability and promoting development. Due to its unique geographical conditions, the Yellow River basin has been facing huge ecological risk pressure. In the affected area of the Lower Yellow River (AALYR) as an agricultural hub, ecological protection has gradually become a key factor restricting the development of cities and agriculture. Taking AALYR as an example, the landscape ecological risk assessment (LERA) system is established based on three aspects “natural environment—human society—landscape pattern”. We construct a comprehensive cumulative resistance surface based on the risk assessment results as the basis for the future study. Ecological corridors are identified by minimum cumulative resistance (MCR) models to establish and optimize Ecological security pattern (ESP) in the AALYR. We found that the landscape ecological risks (LER) in the study area show a uniform spatial distribution, with a slightly higher distribution in the northeast than the southwest. The ecological risk levels are generally high in AALYR, indicating a more severe risk problem in this area. A total of 56 ecological sources were identified, with a total area of 21176 km2. The ecological sensitivity of AALYR was high, and 99 ecological corridors and 59 ecological nodes were extracted. Ecological corridors and nodes were consistently and densely distributed throughout the study area. The network analysis method improves the stability of the network structure after optimization. Based on the key components of the ESP, with the combination of geographical characteristics and local policy planning guidance, we constructed the “One Belt and One Axis, Two Cores and Two Corridors, Four zones” ESP. The study results may offer guidance and suggestions for the construction of ESP and ecological environment protection system in the world’s major river basins, and may also provide information for ecological planning of other similar river basins in the world

Analysis of Long Noncoding RNAs in Aila-Induced Non-Small Cell Lung Cancer Inhibition

Non-small cell lung cancer (NSCLC) has the highest morbidity and mortality among all carcinomas. However, it is difficult to diagnose in the early stage, and current therapeutic efficacy is not ideal. Although numerous studies have revealed that Ailanthone (Aila), a natural product, can inhibit multiple cancers by reducing cell proliferation and invasion and inducing apoptosis, the mechanism by which Aila represses NSCLC progression in a time-dependent manner remains unclear. In this study, we observed that most long noncoding RNAs (lncRNAs) were either notably up- or downregulated in NSCLC cells after treatment with Aila. Moreover, alterations in lncRNA expression induced by Aila were crucial for the initiation and metastasis of NSCLC. Furthermore, in our research, expression of DUXAP8 was significantly downregulated in NSCLC cells after treatment with Aila and regulated expression levels of EGR1. In conclusion, our findings demonstrate that Aila is a potent natural suppressor of NSCLC by modulating expression of DUXAP8 and EGR1

PgtE Enzyme of Salmonella enterica Shares the Similar Biological Roles to Plasminogen Activator (Pla) in Interacting With DEC-205 (CD205), and Enhancing Host Dissemination and Infectivity by Yersinia pestis

Yersinia pestis, the cause of plague, is a newly evolved Gram-negative bacterium. Through the acquisition of the plasminogen activator (Pla), Y. pestis gained the means to rapidly disseminate throughout its mammalian hosts. It was suggested that Y. pestis utilizes Pla to interact with the DEC-205 (CD205) receptor on antigen-presenting cells (APCs) to initiate host dissemination and infection. However, the evolutionary origin of Pla has not been fully elucidated. The PgtE enzyme of Salmonella enterica, involved in host dissemination, shows sequence similarity with the Y. pestis Pla. In this study, we demonstrated that both Escherichia coli K-12 and Y. pestis bacteria expressing the PgtE-protein were able to interact with primary alveolar macrophages and DEC-205-transfected CHO cells. The interaction between PgtE-expressing bacteria and DEC-205-expressing transfectants could be inhibited by the application of an anti-DEC-205 antibody. Moreover, PgtE-expressing Y. pestis partially re-gained the ability to promote host dissemination and infection. In conclusion, the DEC-205-PgtE interaction plays a role in promoting the dissemination and infection of Y. pestis, suggesting that Pla and the PgtE of S. enterica might share a common evolutionary origin.Peer reviewe

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements