A stochastic user-operator assignment game for microtransit service evaluation: A case study of Kussbus in Luxembourg

This paper proposes a stochastic variant of the stable matching model from Rasulkhani and Chow [1] which allows microtransit operators to evaluate their operation policy and resource allocations. The proposed model takes into account the stochastic nature of users' travel utility perception, resulting in a probabilistic stable operation cost allocation outcome to design ticket price and ridership forecasting. We applied the model for the operation policy evaluation of a microtransit service in Luxembourg and its border area. The methodology for the model parameters estimation and calibration is developed. The results provide useful insights for the operator and the government to improve the ridership of the service.Comment: arXiv admin note: substantial text overlap with arXiv:1912.0198

Does urbanization have spatial spillover effect on poverty reduction: empirical evidence from rural China

In light of a scarcity of research on the spatial effects of urbanization on poverty reduction, this study uses panel data on 30 provinces in China from 2009 to 2019 to construct a system of indices to assess poverty that spans the four dimensions of the economy, education, health, and living. We use the spatial autocorrelation test and the spatial Durbin model (SDM) to analyze the spatial effects of urbanization on poverty reduction in these different dimensions. The main conclusions are as follows: (a) China’s urbanization has the characteristics of spatial aggregation and a spatial spillover effect. (b) Different dimensions of poverty had the attributes of spatial agglomeration, and Moran’s index of a reduction in economic poverty was the highest. Under the SDM, the different dimensions of poverty also showed a significant positive spatial correlation. (c) Urbanization has a significant effect on poverty reduction along the dimensions of the economy, education, and living, but has little effect on reducing health poverty. It has a spatial spillover effect on poverty reduction in economic and living contexts. (d) There were spatial differences in the effect of urbanization on relieving economic and living-related poverty

Molecular Basis of PIP2-dependent Conformational Switching of Phosphorylated CD44 in binding FERM

Association of the cellular adhesive protein CD44 and the N-terminal (FERM) domain of cytoskeleton adaptors is critical for cell proliferation, migration and signaling. Phosphorylation of the cytoplasmic domain (CTD) of CD44 acts as an important regulator of the protein association, but the structural transformation and dynamics mechanism remain enigmatic. In this study, extensive coarse-grained simulations were employed to explore the molecular details in the formation of CD44-FERM complex under S291 and S325 phosphorylation, a modification path known to exert reciprocal effects on the protein association. We find that phosphorylation of S291 inhibits complexation by causing the CTD of CD44 to adopt a more closed structure. In contrast, S325 phosphorylation liberates the CD44-CTD from the membrane surface and promotes the linkage with FERM. The phosphorylation-driven transformation is found to occur in a PIP2-dependent manner, with PIP2 effecting the relative stability of the closed and open conformation, and a replacement of PIP2 by POPS greatly abrogates this effect. The revealed interdependent regulation mechanism by phosphorylation and PIP2 in the association of CD44 and FERM further strengthens our understanding of the molecular basis of cellular signaling and migration.</p

MedDiffusion: Boosting Health Risk Prediction via Diffusion-based Data Augmentation

Health risk prediction is one of the fundamental tasks under predictive modeling in the medical domain, which aims to forecast the potential health risks that patients may face in the future using their historical Electronic Health Records (EHR). Researchers have developed several risk prediction models to handle the unique challenges of EHR data, such as its sequential nature, high dimensionality, and inherent noise. These models have yielded impressive results. Nonetheless, a key issue undermining their effectiveness is data insufficiency. A variety of data generation and augmentation methods have been introduced to mitigate this issue by expanding the size of the training data set through the learning of underlying data distributions. However, the performance of these methods is often limited due to their task-unrelated design. To address these shortcomings, this paper introduces a novel, end-to-end diffusion-based risk prediction model, named MedDiffusion. It enhances risk prediction performance by creating synthetic patient data during training to enlarge sample space. Furthermore, MedDiffusion discerns hidden relationships between patient visits using a step-wise attention mechanism, enabling the model to automatically retain the most vital information for generating high-quality data. Experimental evaluation on four real-world medical datasets demonstrates that MedDiffusion outperforms 14 cutting-edge baselines in terms of PR-AUC, F1, and Cohen's Kappa. We also conduct ablation studies and benchmark our model against GAN-based alternatives to further validate the rationality and adaptability of our model design. Additionally, we analyze generated data to offer fresh insights into the model's interpretability

Combination of TRAIL and actinomycin D liposomes enhances antitumor effect in non-small cell lung cancer

The intractability of non-small cell lung cancer (NSCLC) to multimodality treatments plays a large part in its extremely poor prognosis. Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) is a promising cytokine for selective induction of apoptosis in cancer cells; however, many NSCLC cell lines are resistant to TRAIL-induced apoptosis. The therapeutic effect can be restored by treatments combining TRAIL with chemotherapeutic agents. Actinomycin D (ActD) can sensitize NSCLC cells to TRAIL-induced apoptosis by upregulation of death receptor 4 (DR4) or 5 (DR5). However, the use of ActD has significant drawbacks due to the side effects that result from its nonspecific biodistribution in vivo. In addition, the short half-life of TRAIL in serum also limits the antitumor effect of treatments combining TRAIL and ActD. In this study, we designed a combination treatment of long-circulating TRAIL liposomes and ActD liposomes with the aim of resolving these problems. The combination of TRAIL liposomes and ActD liposomes had a synergistic cytotoxic effect against A-549 cells. The mechanism behind this combination treatment includes both increased expression of DR5 and caspase activation. Moreover, systemic administration of the combination of TRAIL liposomes and ActD liposomes suppressed both tumor formation and growth of established subcutaneous NSCLC xenografts in nude mice, inducing apoptosis without causing significant general toxicity. These results provide preclinical proof-of-principle for a novel therapeutic strategy in which TRAIL liposomes are safely combined with ActD liposomes