Supply Chain and Service Operations with Demand-Side Flexibility

In this thesis, we consider improving supply chain and service systems through demand-side management. In Chapters 1 and 2, we focus on a new notion of flexibility that has emerged in e-commerce called consumer flexibility. Motivated by the fact that some customers may willingly provide flexibility on which product or service they receive in exchange for a reward, firms can design flexible options to leverage this consumer flexibility for significant benefit in their operations. In Chapter 1, we consider the context of online retailing where consumer flexibility can be realized through opaque selling, where some specific attributes of the products are not revealed to the customer until after purchase. In Chapter 2, we focus on the context of online booking systems for scheduled services where consumer flexibility can be realized through large time windows. The main findings are on the power of limited flexibility using simple flexible options with just a small fraction of customers willing to be flexible. In Chapter 3, we study the issue of congested elevator queuing systems due to the requirement of social distancing during a pandemic. We propose simple interventions for safely managing the elevator queues, which require no programming of the elevator system and only manage passenger behaviors. The key idea is to explicitly or implicitly group passengers going to the same or nearby floor into the same elevator as much as possible. Simulations and stability analysis show that our proposed interventions significantly reduce queue length and wait time

STABILITY ANALYSIS OF THE GRAVITY ANCHORAGE OF A SUSPENSION BRIDGE BASED ON LARGE-SCALE FIELD TESTS

The stability of gravity anchorages is critical to the safe operation of suspension bridges. The purpose of this paper is to study the stability of a gravity anchorage under the tension of main cables. Large-scale load tests and direct shear tests under the nature state and the saturated state were carried out in the adit at the bottom of the gravity anchorage, because the bottom surface of the gravity anchorage is below the design water level of a reservoir to be built. Representative rock samples in the anchorage area were selected for indoor tests. The basic parameters of the rock mass and the characteristic value of subsoil bearing capacity were obtained based on the field and indoor tests results. The static theory was used to calculate the anti-sliding stability coefficient, anti- overturning stability coefficient and contact stress of the gravity anchorage. The finite element software was used to calculate the horizontal displacement, vertical settlement and contact stress of the gravity anchorage. The calculation results met the relevant requirements, and it can be considered that the gravity anchorage was stable under the tension of main cables. It would provide a reference for the stability study of the gravity anchorage of suspension bridges

Pyrolysis gas as a carbon source for biogas production via anaerobic digestion

Carbon is an important resource for anaerobes to enhance biogas production. In this study, the possibility of using simulated pyrolysis gas (SPG) as a carbon source for biogas production was investigated. The effects of stirring speed (SS), gas holding time (GHT), and H2 addition on biomethanation of SPG were evaluated. The diversity and structure of microbial communities were also analyzed under an illumina MiSeq platform. Results indicated that at a GHT of 14 h and an SS at 400 rpm, SPG with up to 64.7% CH4could be bio-upgraded to biogas. Gas–liquid mass transfer is the limitation for SPG biomethanation. For the first time, it has been noticed that the addition of H2 can bioupgrade SPG to high quality biogas (with 91.1% CH4). Methanobacterium was considered as a key factor in all reactors. This study provides an idea and alternative way to convert lignocellulosic biomass and solid organic waste into energy (e.g., pyrolysis was used as a pretreatment to produce pyrolysis gas from biomass, and then, pyrolysis gas was bioupgraded to higher quality biogas via anaerobic digestion)

Integrative bioinformatics approaches to establish potential prognostic immune-related genes signature and drugs in the non-small cell lung cancer microenvironment

Introduction: Research has revealed that the tumor microenvironment (TME) is associated with the progression of malignancy. The combination of meaningful prognostic biomarkers related to the TME is expected to be a reliable direction for improving the diagnosis and treatment of non-small cell lung cancer (NSCLC).Method and Result: Therefore, to better understand the connection between the TME and survival outcomes of NSCLC, we used the “DESeq2” R package to mine the differentially expressed genes (DEGs) of two groups of NSCLC samples according to the optimal cutoff value of the immune score through the ESTIMATE algorithm. A total of 978 up-DEGs and 828 down-DEGs were eventually identified. A fifteen-gene prognostic signature was established via LASSO and Cox regression analysis and further divided the patients into two risk sets. The survival outcome of high-risk patients was significantly worse than that of low-risk patients in both the TCGA and two external validation sets (p-value < 0.05). The gene signature showed high predictive accuracy in TCGA (1-year area under the time-dependent ROC curve (AUC) = 0.722, 2-year AUC = 0.708, 3-year AUC = 0.686). The nomogram comprised of the risk score and related clinicopathological information was constructed, and calibration plots and ROC curves were applied, KEGG and GSEA analyses showed that the epithelial-mesenchymal transition (EMT) pathway, E2F target pathway and immune-associated pathway were mainly involved in the high-risk group. Further somatic mutation and immune analyses were conducted to compare the differences between the two groups. Drug sensitivity provides a potential treatment basis for clinical treatment. Finally, EREG and ADH1C were selected as the key prognostic genes of the two overlapping results from PPI and multiple Cox analyses. They were verified by comparing the mRNA expression in cell lines and protein expression in the HPA database, and clinical validation further confirmed the effectiveness of key genes.Conclusion: In conclusion, we obtained an immune-related fifteen-gene prognostic signature and potential mechanism and sensitive drugs underling the prognosis model, which may provide accurate prognosis prediction and available strategies for NSCLC

p97/VCP is highly expressed in the stem-like cells of breast cancer and controls cancer stemness partly through the unfolded protein response

p97/VCP, an evolutionarily concerned ATPase, partakes in multiple cellular proteostatic processes, including the endoplasmic reticulum (ER)-associated protein degradation (ERAD). Elevated expression of p97 is common in many cancers and is often associated with poor survival. Here we report that the levels of p97 positively correlated with the histological grade, tumor size, and lymph node metastasis in breast cancers. We further examined p97 expression in the stem-like cancer cells or cancer stem cells (CSCs), a cell population that purportedly underscores cancer initiation, therapeutic resistance, and recurrence. We found that p97 was consistently at a higher level in the CD4

TENSOR GENERALIZED ESTIMATING EQUATIONS FOR LONGITUDINAL IMAGING ANALYSIS.

Longitudinal neuroimaging studies are becoming increasingly prevalent, where brain images are collected on multiple subjects at multiple time points. Analyses of such data are scientifically important, but also challenging. Brain images are in the form of multidimensional arrays, or tensors, which are characterized by both ultrahigh dimensionality and a complex structure. Longitudinally repeated images and induced temporal correlations add a further layer of complexity. Despite some recent efforts, there exist very few solutions for longitudinal imaging analyses. In response to the increasing need to analyze longitudinal imaging data, we propose several tensor generalized estimating equations (GEEs). The proposed GEE approach accounts for intra-subject correlation, and an imposed low-rank structure on the coefficient tensor effectively reduces the dimensionality. We also propose a scalable estimation algorithm, establish the asymptotic properties of the solution to the tensor GEEs, and investigate sparsity regularization for the purpose of region selection. We demonstrate the proposed method using simulations and by analyzing a real data set from the Alzheimer's Disease Neuroimaging Initiative

A fully functional Ramsey-CPT atomic clock

The abstract presents a fully functional Ramsey-CPT atomic clock, which has the characteristics of compact structure, small volume, low cost, strong adaptability, high stability, convenient for adjustment, unique design, and easy-to-commercialization. The Ramsey-CPT atomic clock combines the method of separated oscillatory fields and the phenomenon of coherent population trapping, so as to obtain narrower line width and better signal-to-noise ratio of the resonance signal for improving the frequency stability. It not only keeps the advantages of miniaturization and low power of the CPT atomic clock, but also can obtain higher frequency stability than CPT atomic clock about one order of magnitude. ? 2011 IEEE.EI