Online Vertex-Weighted Bipartite Matching: Beating 1-1/e with Random Arrivals

We introduce a weighted version of the ranking algorithm by Karp et al. (STOC 1990), and prove a competitive ratio of 0.6534 for the vertex-weighted online bipartite matching problem when online vertices arrive in random order. Our result shows that random arrivals help beating the 1-1/e barrier even in the vertex-weighted case. We build on the randomized primal-dual framework by Devanur et al. (SODA 2013) and design a two dimensional gain sharing function, which depends not only on the rank of the offline vertex, but also on the arrival time of the online vertex. To our knowledge, this is the first competitive ratio strictly larger than 1-1/e for an online bipartite matching problem achieved under the randomized primal-dual framework. Our algorithm has a natural interpretation that offline vertices offer a larger portion of their weights to the online vertices as time goes by, and each online vertex matches the neighbor with the highest offer at its arrival

Simulating the Integration of Urban Air Mobility into Existing Transportation Systems: A Survey

Urban air mobility (UAM) has the potential to revolutionize transportation in metropolitan areas, providing a new mode of transportation that could alleviate congestion and improve accessibility. However, the integration of UAM into existing transportation systems is a complex task that requires a thorough understanding of its impact on traffic flow and capacity. In this paper, we conduct a survey to investigate the current state of research on UAM in metropolitan-scale traffic using simulation techniques. We identify key challenges and opportunities for the integration of UAM into urban transportation systems, including impacts on existing traffic patterns and congestion; safety analysis and risk assessment; potential economic and environmental benefits; and the development of shared infrastructure and routes for UAM and ground-based transportation. We also discuss the potential benefits of UAM, such as reduced travel times and improved accessibility for underserved areas. Our survey provides a comprehensive overview of the current state of research on UAM in metropolitan-scale traffic using simulation and highlights key areas for future research and development

Gene Order Phylogeny and the Evolution of Methanogens

Methanogens are a phylogenetically diverse group belonging to Euryarchaeota. Previously, phylogenetic approaches using large datasets revealed that methanogens can be grouped into two classes, “Class I” and “Class II”. However, some deep relationships were not resolved. For instance, the monophyly of “Class I” methanogens, which consist of Methanopyrales, Methanobacteriales and Methanococcales, is disputable due to weak statistical support. In this study, we use MSOAR to identify common orthologous genes from eight methanogen species and a Thermococcale species (outgroup), and apply GRAPPA and FastME to compute distance-based gene order phylogeny. The gene order phylogeny supports two classes of methanogens, but it differs from the original classification of methanogens by placing Methanopyrales and Methanobacteriales together with Methanosarcinales in Class II rather than with Methanococcales. This study suggests a new classification scheme for methanogens. In addition, it indicates that gene order phylogeny can complement traditional sequence-based methods in addressing taxonomic questions for deep relationships

Jejunal Metabolic Responses to Escherichia coli Infection in Piglets

This study aimed to investigate the jejunal metabolic variations in enterotoxigenic Escherichia coli (ETEC)-infected piglets. Piglets were infected with 1 × 1010 CFUs (colony-forming units) of ETEC W25K and assigned into diarrheal, recovered, control, and resistant groups. Jejunal samples were harvested at day 6 and metabolic profiles were analyzed via gas chromatography coupled to time-of-flight mass spectrometry (GC/TOFMS). The results showed that 33 metabolites in the jejunum were identified in ETEC-induced diarrhea, including amino acids, fatty acids, sugars, and organic acids. Compared with the control, resistant, and recovered piglets, diarrheal piglets showed higher concentrations of 4-aminobutyric acid (GABA) and glycine in the jejunum. Compared with the control and resistant piglets, six metabolites were markedly decreased in diarrheal piglets, including ornithine, asparagine, glutamine, citric acid, citrulline, and lysine. Collectively, this study provides insights into jejunal metabolic response to ETEC infection and ETEC induced diarrhea in piglets

Effect of Eucommia ulmoides Leaf Extract on Growth Performance, Carcass Traits, Parameters of Oxidative Stress, and Lipid Metabolism in Broiler Chickens

Eucommia ulmoides bark has been traditionally used as a Chinese medicine to attenuate stress, but the leaf, which is rich in polyphenols and polysaccharides, has been rarely used. This study aimed to investigate the effect of Eucommia ulmoides leaf extracts (EULEs) on oxidative stress and meat quality of broilers. A total of 252 broilers were randomly divided into 3 treatments and fed with a control basal diet (CON), or a diet containing 250 mg/kg or 1,000 mg/kg of EULE for 51 days. Results showed that dietary supplementation of 250 mg/kg EULE increased significantly the average daily gain of broilers in the early stage (1–21 days), while 250 mg/kg or 1,000 mg/kg of EULE decreased the feed conversion ratio in the whole period (P < 0.05). Supplementation of 250 mg/kg EULE reduced the level of MDA in the liver (P < 0.05), while 1,000 mg/kg EULE decreased the serum level of MDA (P < 0.05), and the HDL level in serum was increased by 250 mg/kg or 1,000 mg/kg EULE (P < 0.05). Additionally, 250 mg/kg EULE decreased abdominal fat ratio and serum triglyceride (TC) level in broilers, while 250 or 1,000 mg/kg of EULE reduced drip loss in breast muscle (P < 0.05), and 1,000 mg/kg EULE reduced the cooking loss in thigh muscle (P < 0.05). In conclusion, dietary supplementation of 250 mg/kg of EULE could attenuate oxidative stress and improve the growth performance and meat quality in broilers

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets

Recently, pre-trained foundation models have enabled significant advancements in multiple fields. In molecular machine learning, however, where datasets are often hand-curated, and hence typically small, the lack of datasets with labeled features, and codebases to manage those datasets, has hindered the development of foundation models. In this work, we present seven novel datasets categorized by size into three distinct categories: ToyMix, LargeMix and UltraLarge. These datasets push the boundaries in both the scale and the diversity of supervised labels for molecular learning. They cover nearly 100 million molecules and over 3000 sparsely defined tasks, totaling more than 13 billion individual labels of both quantum and biological nature. In comparison, our datasets contain 300 times more data points than the widely used OGB-LSC PCQM4Mv2 dataset, and 13 times more than the quantum-only QM1B dataset. In addition, to support the development of foundational models based on our proposed datasets, we present the Graphium graph machine learning library which simplifies the process of building and training molecular machine learning models for multi-task and multi-level molecular datasets. Finally, we present a range of baseline results as a starting point of multi-task and multi-level training on these datasets. Empirically, we observe that performance on low-resource biological datasets show improvement by also training on large amounts of quantum data. This indicates that there may be potential in multi-task and multi-level training of a foundation model and fine-tuning it to resource-constrained downstream tasks

Identification and Differential Expression of MicroRNAs during Metamorphosis of the Japanese Flounder (Paralichthys olivaceus)

BACKGROUND: MicroRNAs (miRNAs) are a class of endogenous small non-coding RNAs of 20-25 nucleotides that play a key role in diverse biological processes. Japanese flounder undergo dramatic metamorphosis in their early development. The metamorphosis is characterized by morphological transformation from a bilaterally symmetrical to an asymmetrical body shape concomitant with extensive morphological and physiological remodeling of organs. So far, only a few miRNAs have been identified in fish and there are very few reports about the Japanese flounder miRNA. METHODOLOGY/PRINCIPAL FINDINGS: Solexa sequencing technology was used to perform high throughput sequencing of the small RNA library from the metamorphic period of Japanese flounder. Subsequently, aligning these sequencing data with metazoan known miRNAs, we characterized 140 conserved miRNAs and 57 miRNA: miRNA* pairs from the small RNA library. Among these 57 miRNA: miRNA* pairs, twenty flounder miRNA precursors were amplified from genomic DNA. We also demonstrated evolutionary conservation of Japanese flounder miRNAs and miRNA* in the animal evolution process. Using miRNA microarrays, we identified 66 differentially expressed miRNAs at two metamorphic stages (17 and 29 days post hatching) of Japanese flounder. The results show that miRNAs might play a key role in regulating gene expression during Japanese flounder metamorphosis. CONCLUSIONS/SIGNIFICANCE: We identified a large number of miRNAs during flounder metamorphosis, some of which are differentially expressed at two different metamorphic stages. The study provides an opportunity for further understanding of miRNA function in the regulation of flounder metamorphosis and gives us clues for further studies of the mechanisms of metamorphosis in Japanese flounder