Spatio-Temporal Pricing for Ridesharing Platforms

Ridesharing platforms have radically changed the way people get around in urban areas, but there remain challenges undercutting the mission of “making transportation as reliable as running water.” A particular concern is that drivers strategize: calling riders to find out their destinations and canceling trips that are not worthwhile, declining trips and chasing surge prices in neighboring areas, and going off-line before large events will end in anticipation of a price increase. In this work, we show that such strategic behaviors are symptoms of inefficiencies in the pricing and dispatching rules governing today's platforms. We propose the Spatio-Temporal Pricing mechanism, which solves for the welfare-optimal matching of drivers to trips, and sets prices that are appropriately smooth in both space and time such that the best thing for drivers to do is accept any proposed trip dispatch. This demonstrates that ridesharing platforms can succeed in optimally orchestrating trips and providing reliable transpiration for riders, while still leaving drivers with the flexibility to decide how to work.

VARIOUS KINDS OF MATRICES IN CYCLOTOMIC GRAPHS

The component matrix, Laplacian matrix, Distance matrix, Peripheral distance matrix, Distance Laplacian of the cyclotomic graphs and some properties are found. The D-energy, $D_{p}$-energy, $D^{L}$-energy and some indices of the cyclotomic graphs are determined. For the real symmetric matrices, matrices that attain the maximum $L, L_{s}$ and the minimum S are calculated. The Hausdorff distance and optimal matching distance of the cyclotomic graphs are evaluated.

Optimal Matching in Julia Using Distributed Computing: Time Use Data (ATUS)

A brief tutorial on how to run optimal matching in Julia. The performance gains: it is twice faster than TraMineR on a dataset of about 20000 sequences with 96 steps each.

Association Analysis between Introns and mRNAs in Caenorhabditis elegans Genes with Different Expression Levels

Background: Introns are ubiquitous in pre-mRNA but are often overlooked. They also play an important role in the regulation of gene expression. Objective and Method : We mainly use the improved Smith-Waterman local alignment approach to compare the optimal matching regions between introns and mRNA sequences in Caenorhabditis elegans (C. elegans) genes with high and low expression. Results We found that the relative matching frequency distributions of all genes lie exactly between highly and lowly expressed genes, indicating that introns in highly and lowly expressed genes have different biological functions. Highly expressed genes have higher matching strengths on mRNA sequences than genes expressed at lower levels; the remarkably matched regions appear in UTR regions, particularly in the 3'UTR. The optimal matching frequency distributions have obvious differences in functional regions of the translation initiation and termination sites in highly and lowly expressed genes. The mRNA sequences with CpG islands tend to have stronger relative matching frequency distributions, especially in highly expressed genes. Additionally, the sequence characteristics of the optimal matched segments are consistent with those of the miRNAs, and they are considered a type of functional RNA segment. Conclusion: Introns in highly and lowly expressed genes contribute to the recognition translation initiation sites and translation termination sites. Moreover, our results suggest that the potential matching relationships between introns and mRNA sequences in highly and lowly expressed genes are significantly different and indicate that the matching strength correlates with the ability of introns to enhance gene expression.

Improving Matching Accuracy of Underwater Gravity Matching Navigation Based on Iterative Optimal Annulus Point Method with a Novel Grid Topology

In this study, we improve the matching accuracy of underwater gravity matching navigation. Firstly, the Iterative Optimal Annulus Point (IOAP) method with a novel grid topology is proposed for breaking through the inherent grid structure limit of the canonical gravity matching algorithm and enhancing its underwater gravity matching accuracy. The theory of IOAP is as follows: (1) small-annulus matching and positioning mechanism on the tracking starting point is developed by employing the starting point and drift error of the INS (Inertial Navigation System), the fixed rotation angle, etc. The optimal matching location of the starting point is obtained by matching and comparing the matched points in this small-annulus grid, which contributes to heightening the initial-position error insensitivity of the algorithms. (2) Variable-angle three-layer annulus matching and positioning mechanisms on the tracking ending point were constructed by using the optimal matching location of the starting point and combining the tracking direction-and-distance information of the INS and the cumulative drift error, etc. It is used to generate the annulus matching points with the ring-type grid topology. (3) The optimal matching position of the ending point in this annulus is obtained by iteratively calculating the evaluation index value of the matching points and following the evaluation index optimal rule. Secondly, we comprehensively consider the main performance evaluation indexes of the underwater gravity matching algorithms, such as the statistical indicators of the matching accuracy, the average matching time and the matching success rate, and take them as a basis of the pros and cons of the matching analysis. Furthermore, under conditions that include different scale searching regions or different reference-angle ring radii, the statistical results verify that the IOAP had a different matching ability and better robustness. Finally, several trajectories with the starting points from different areas and the ending points in different gravity ranges are tested and compared to carry out the numerical simulations. These results indicate that the IOAP has many advantages, such as a high matching accuracy and strong positioning applicability in different gravity regions. Compared with the TERCOM (terrain contour matching algorithm), its average matching accuracy was the highest, increased by 40.39%.

The potential of family-free rearrangements towards gene orthology inference

Recently, we proposed an efficient ILP formulation [Rubert DP, Martinez FV, Braga MDV, Natural family-free genomic distance, Algorithms Mol Biol 16:4, 2021] for exactly computing the rearrangement distance of two genomes in a family-free setting. In such a setting, neither prior classification of genes into families, nor further restrictions on the genomes are imposed. Given two genomes, the mentioned ILP computes an optimal matching of the genes taking into account simultaneously local mutations, given by gene similarities, and large-scale genome rearrangements. Here, we explore the potential of using this ILP for inferring groups of orthologs across several species. More precisely, given a set of genomes, our method first computes all pairwise optimal gene matchings, which are then integrated into gene families in the second step. Our approach is implemented into a pipeline incorporating the pre-computation of gene similarities. It can be downloaded from gitlab.ub.uni-bielefeld.de/gi/FFGC. We obtained promising results with experiments on both simulated and real data.