Near-Optimal Primal-Dual Algorithms for Quantity-Based Network Revenue Management

We study the canonical quantity-based network revenue management (NRM) problem where the decision-maker must irrevocably accept or reject each arriving customer request with the goal of maximizing the total revenue given limited resources. The exact solution to the problem by dynamic programming is computationally intractable due to the well-known curse of dimensionality. Existing works in the literature make use of the solution to the deterministic linear program (DLP) to design asymptotically optimal algorithms. Those algorithms rely on repeatedly solving DLPs to achieve near-optimal regret bounds. It is, however, time-consuming to repeatedly compute the DLP solutions in real time, especially in large-scale problems that may involve hundreds of millions of demand units. In this paper, we propose innovative algorithms for the NRM problem that are easy to implement and do not require solving any DLPs. Our algorithm achieves a regret bound of $O(\log k)$, where $k$ is the system size. To the best of our knowledge, this is the first NRM algorithm that (i) has an $o(\sqrt{k})$ asymptotic regret bound, and (ii) does not require solving any DLPs

Generalizing Graph ODE for Learning Complex System Dynamics across Environments

Learning multi-agent system dynamics has been extensively studied for various real-world applications, such as molecular dynamics in biology. Most of the existing models are built to learn single system dynamics from observed historical data and predict the future trajectory. In practice, however, we might observe multiple systems that are generated across different environments, which differ in latent exogenous factors such as temperature and gravity. One simple solution is to learn multiple environment-specific models, but it fails to exploit the potential commonalities among the dynamics across environments and offers poor prediction results where per-environment data is sparse or limited. Here, we present GG-ODE (Generalized Graph Ordinary Differential Equations), a machine learning framework for learning continuous multi-agent system dynamics across environments. Our model learns system dynamics using neural ordinary differential equations (ODE) parameterized by Graph Neural Networks (GNNs) to capture the continuous interaction among agents. We achieve the model generalization by assuming the dynamics across different environments are governed by common physics laws that can be captured via learning a shared ODE function. The distinct latent exogenous factors learned for each environment are incorporated into the ODE function to account for their differences. To improve model performance, we additionally design two regularization losses to (1) enforce the orthogonality between the learned initial states and exogenous factors via mutual information minimization; and (2) reduce the temporal variance of learned exogenous factors within the same system via contrastive learning. Experiments over various physical simulations show that our model can accurately predict system dynamics, especially in the long range, and can generalize well to new systems with few observations

Zimp7 and Zimp10, two novel PIAS-like proteins, function as androgen receptor coregulators

The androgen receptor (AR) plays a critical role in male sexual development and in normal and malignant prostate cell growth and survival. It has been shown that AR transcriptional activation is regulated through interactions with a variety of transcriptional co-regulators. The Protein Inhibitors of Activated STATs (PIAS) are transcriptional co-regulators, and have been shown to modulate AR-mediated transcription. In this brief, we summarize our recent studies on two novel PIAS-like proteins, Zimp7 and Zimp10. Particularly, we address the functional interactions between the AR and these two proteins, and potential mechanisms by which they regulate AR mediated transcription. In addition, we explore potential roles of Zimp10 in transcriptional regulation in vivo using a recent Zimp10 knockout mouse model. Taken together, our findings thus far suggest that Zimp7 and Zimp10 are functionally non-redundant and share unique characteristics that have not been described for the PIAS family. Further investigation into the functional roles of these two PIAS-like proteins may help to better understand prostate cancer progression, and yield possible new targets for therapeutic intervention

Backbone exponent for two-dimensional percolation

We derive an exact expression for the celebrated backbone exponent for Bernoulli percolation in dimension two at criticality. It turns out to be a root of an elementary function. Contrary to previously known arm exponents for this model, which are all rational, it has a transcendental value. Our derivation relies on the connection to the SLE$_\kappa$ bubble measure, the coupling between SLE and Liouville quantum gravity, and the integrability of Liouville conformal field theory. Along the way, we derive a formula not only for $\kappa=6$ (corresponding to percolation), but for all $\kappa \in (4,8)$.Comment: 63 pages, 17 figure

A multi-continuum model for simulating in-situ conversion process in low-medium maturity shale oil reservoir

In-situ conversion is proposed applicable for low-medium maturity shale oil reservoir. However, parallel chemical kinetic reactions and evolution of shale pores during in-situ conversion make the numerical simulation a challenging problem. Although shale is typical multiscale and heterogeneous media, few models in previous studies take the difference between organic and inorganic system into consideration, which cannot simulate fluid flow accurately. In this paper, a multi-continuum model, considering coupled thermal-reactive compositional flow, is developed to simulate in-situ conversion process in low-medium maturity shale oil reservoir. The reaction of kerogen and hydrocarbon is quantified using kinetic reaction model. The evolution of fluid composition and shale properties are also incorporated. The accuracy of multiple-interacting-continua model and compositional model are demonstrated by comparing with commercial software and analytical solution. Then, the typical hexagon vertical well heating pattern is simulated and the feasibility is evaluated from an economic aspect. Finally, a series of case studies are conducted to investigate the impact of operation parameters on shale oil production.Cited as: Wang, Z., Yao, J., Sun, H, Yan, X., Yang, Y. A multi-continuum model for simulating in-situ conversion process in low-medium maturity shale oil reservoir. Advances in Geo-Energy Research, 2021, 5(4): 456-464, doi: 10.46690/ager.2021.04.1

Cyclin D1 and p16 expression in recurrent nasopharyngeal carcinoma

Abstract Background Cyclin D1 and p16 are involved in the regulation of G1 checkpoint and may play an important role in the tumorigenesis of nasopharyngeal carcinoma (NPC). Previous studies have examined the level of expression of cyclin D1 and p16 in primary untreated NPC but no such information is available for recurrent NPC. We set out in this study to examine the expression level of cyclin D1 and p16 in recurrent NPC that have failed previous treatment with radiation +/- chemotherapy. Patients and methods A total of 42 patients underwent salvage nasopharyngectomy from 1984 to 2001 for recurrent NPC after treatment failure with radiation +/- chemotherapy. Twenty-seven pathologic specimens were available for immunohistochemical study using antibodies against cyclin D1 and p16. Results Positive expression of cyclin D1 was observed in 7 of 27 recurrent NPC specimens (26%) while positive p16 expression was seen in only 1 of 27 recurrent NPC (4%). Conclusion While the level of expression of cyclin D1 in recurrent NPC was similar to that of previously untreated head and neck cancer, the level of p16 expression in recurrent NPC samples was much lower than that reported for previously untreated cancer. The finding that almost all (96%) of the recurrent NPC lack expression of p16 suggested that loss of p16 may confer a survival advantage by making cancer cells more resistant to conventional treatment with radiation +/- chemotherapy. Further research is warranted to investigate the clinical use of p16 both as a prognostic marker and as a potential therapeutic target

Histocompatibility and Long-Term Results of the Follicular Unit-Like Wigs after Xenogeneic Hair Transplantation: An Experimental Study in Rabbits

Objective. This study was designed to observe the histocompatibility and long-term results of wigs after xenogeneic hair transplantation and to explore the possibility of industrial products in clinical application. Methods. The human hair and melted medical polypropylene were preceded into the follicular unit-like wigs according to the natural follicular unit by extrusion molding. 12 New Zealand rabbits were used as experimental animals for wigs transplantation. The histocompatibility of polypropylene and human hair was observed by H&E staining and scanning electron microscope. The loss rate of wigs was calculated to evaluate the long-term result after transplantation. Results. Mild infiltration by inflammatory cells around the polypropylene and human hair were seen during the early period after transplantation, accompanied with local epithelial cell proliferation. The inflammatory cells were decreased after 30 days with increased collagen fibers around the polypropylene and human hair. The follicular unit-like wigs maintained a good histocompatibility in one year. The degradation of hair was not significant. The loss rate of wigs was 4.1 ± 4.0% in one year. The appearance of hair was satisfactory. Conclusions. We successfully developed a follicular unit-like wigs, which were made of xenogeneic human hair with medical polypropylene, showing a good histocompatibility, a low loss rate, and satisfactory appearance in a year after transplantation. The follicular unit-like wigs may have prospective industrial products in clinical application

Tumor promoter TPA activates Wnt/β-catenin signaling in a casein kinase 1-dependent manner.

The tumor promoter 12-O-tetra-decanoylphorbol-13-acetate (TPA) has been defined by its ability to promote tumorigenesis on carcinogen-initiated mouse skin. Activation of Wnt/β-catenin signaling has a decisive role in mouse skin carcinogenesis, but it remains unclear how TPA activates Wnt/β-catenin signaling in mouse skin carcinogenesis. Here, we found that TPA could enhance Wnt/β-catenin signaling in a casein kinase 1 (CK1) ε/δ-dependent manner. TPA stabilized CK1ε and enhanced its kinase activity. TPA further induced the phosphorylation of LRP6 at Thr1479 and Ser1490 and the formation of a CK1ε-LRP6-axin1 complex, leading to an increase in cytosolic β-catenin. Moreover, TPA increased the association of β-catenin with TCF4E in a CK1ε/δ-dependent way, resulting in the activation of Wnt target genes. Consistently, treatment with a selective CK1ε/δ inhibitor SR3029 suppressed TPA-induced skin tumor formation in vivo, probably through blocking Wnt/β-catenin signaling. Taken together, our study has identified a pathway by which TPA activates Wnt/β-catenin signaling

Loss of androgen signaling in mesenchymal sonic hedgehog responsive cells diminishes prostate development, growth, and regeneration.

Prostate embryonic development, pubertal and adult growth, maintenance, and regeneration are regulated through androgen signaling-mediated mesenchymal-epithelial interactions. Specifically, the essential role of mesenchymal androgen signaling in the development of prostate epithelium has been observed for over 30 years. However, the identity of the mesenchymal cells responsible for this paracrine regulation and related mechanisms are still unknown. Here, we provide the first demonstration of an indispensable role of the androgen receptor (AR) in sonic hedgehog (SHH) responsive Gli1-expressing cells, in regulating prostate development, growth, and regeneration. Selective deletion of AR expression in Gli1-expressing cells during embryogenesis disrupts prostatic budding and impairs prostate development and formation. Tissue recombination assays showed that urogenital mesenchyme (UGM) containing AR-deficient mesenchymal Gli1-expressing cells combined with wildtype urogenital epithelium (UGE) failed to develop normal prostate tissue in the presence of androgens, revealing the decisive role of AR in mesenchymal SHH responsive cells in prostate development. Prepubescent deletion of AR expression in Gli1-expressing cells resulted in severe impairment of androgen-induced prostate growth and regeneration. RNA-sequencing analysis showed significant alterations in signaling pathways related to prostate development, stem cells, and organ morphogenesis in AR-deficient Gli1-expressing cells. Among these altered pathways, the transforming growth factor β1 (TGFβ1) pathway was up-regulated in AR-deficient Gli1-expressing cells. We further demonstrated the activation of TGFβ1 signaling in AR-deleted prostatic Gli1-expressing cells, which inhibits prostate epithelium growth through paracrine regulation. These data demonstrate a novel role of the AR in the Gli1-expressing cellular niche for regulating prostatic cell fate, morphogenesis, and renewal, and elucidate the mechanism by which mesenchymal androgen-signaling through SHH-responsive cells elicits the growth and regeneration of prostate epithelium