Advances in Learning Bayesian Networks of Bounded Treewidth

This work presents novel algorithms for learning Bayesian network structures with bounded treewidth. Both exact and approximate methods are developed. The exact method combines mixed-integer linear programming formulations for structure learning and treewidth computation. The approximate method consists in uniformly sampling $k$-trees (maximal graphs of treewidth $k$), and subsequently selecting, exactly or approximately, the best structure whose moral graph is a subgraph of that $k$-tree. Some properties of these methods are discussed and proven. The approaches are empirically compared to each other and to a state-of-the-art method for learning bounded treewidth structures on a collection of public data sets with up to 100 variables. The experiments show that our exact algorithm outperforms the state of the art, and that the approximate approach is fairly accurate.Comment: 23 pages, 2 figures, 3 table

Efficient learning of Bayesian networks with bounded tree-width

Learning Bayesian networks with bounded tree-width has attracted much attention recently, because low tree-width allows exact inference to be performed efficiently. Some existing methods [24,29] tackle the problem by using k-trees to learn the optimal Bayesian network with tree-width up to k. Finding the best k-tree, however, is computationally intractable. In this paper, we propose a sampling method to efficiently find representative k-trees by introducing an informative score function to characterize the quality of a k-tree. To further improve the quality of the k-trees, we propose a probabilistic hill climbing approach that locally refines the sampled k-trees. The proposed algorithm can efficiently learn a quality Bayesian network with tree-width at most k. Experimental results demonstrate that our approach is more computationally efficient than the exact methods with comparable accuracy, and outperforms most existing approximate methods

Remote silicate supply regulates spring phytoplankton bloom magnitude in the Gulf of Maine

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Zang, Z., Ji, R., Liu, Y., Chen, C., Li, Y., Li, S., & Davis, C. S. Remote silicate supply regulates spring phytoplankton bloom magnitude in the Gulf of Maine. Limnology and Oceanography Letters, 7, (2022): 277-285, https://doi.org/10.1002/lol2.10245.Spring phytoplankton blooms in the Gulf of Maine (GoM) are sensitive to climate-related local and remote forcing. Nutrient supply through the slope water intrusion has been viewed as critical in regulating the GoM spring blooms, with an assumption that nitrogen is the primary limiting nutrient. In recent years, this paradigm has been challenged, with silicate being recognized as another potential limiting nutrient, but the source of silicate and its associated water mass remain difficult to be determined. In this study, a time series of spring bloom magnitude was constructed using a self-organizing map algorithm, and then correlated with the fluctuation of water composition in the deep Northeast Channel. The results reveal the importance of silicate supply from previously less-recognized deep Scotian Shelf Water inflow. This study offers a new hypothesis for spring bloom regulation, providing a better understanding of mechanisms controlling the spring bloom magnitude in the GoM.This study was supported by NOAA Coastal and Ocean Climate Application (COCA) Program (NA17OAR4310273) and NSF Northeast US Shelf-Long-Term Ecological Research (NES-LTER) Program (OCE-1655686)

Emerging Theranostic Nanomaterials in Diabetes and Its Complications

Diabetes mellitus (DM) refers to a group of metabolic disorders that are characterized by hyperglycemia. Oral subcutaneously administered antidiabetic drugs such as insulin, glipalamide, and metformin can temporarily balance blood sugar levels, however, long-term administration of these therapies is associated with undesirable side effects on the kidney and liver. In addition, due to overproduction of reactive oxygen species and hyperglycemia-induced macrovascular system damage, diabetics have an increased risk of complications. Fortunately, recent advances in nanomaterials have provided new opportunities for diabetes therapy and diagnosis. This review provides a panoramic overview of the current nanomaterials for the detection of diabetic biomarkers and diabetes treatment. Apart from diabetic sensing mechanisms and antidiabetic activities, the applications of these bioengineered nanoparticles for preventing several diabetic complications are elucidated. This review provides an overall perspective in this field, including current challenges and future trends, which may be helpful in informing the development of novel nanomaterials with new functions and properties for diabetes diagnosis and therapy.Peer reviewe

CrossBind: Collaborative Cross-Modal Identification of Protein Nucleic-Acid-Binding Residues

Accurate identification of protein nucleic-acid-binding residues poses a significant challenge with important implications for various biological processes and drug design. Many typical computational methods for protein analysis rely on a single model that could ignore either the semantic context of the protein or the global 3D geometric information. Consequently, these approaches may result in incomplete or inaccurate protein analysis. To address the above issue, in this paper, we present CrossBind, a novel collaborative cross-modal approach for identifying binding residues by exploiting both protein geometric structure and its sequence prior knowledge extracted from a large-scale protein language model. Specifically, our multi-modal approach leverages a contrastive learning technique and atom-wise attention to capture the positional relationships between atoms and residues, thereby incorporating fine-grained local geometric knowledge, for better binding residue prediction. Extensive experimental results demonstrate that our approach outperforms the next best state-of-the-art methods, GraphSite and GraphBind, on DNA and RNA datasets by 10.8/17.3% in terms of the harmonic mean of precision and recall (F1-Score) and 11.9/24.8% in Matthews correlation coefficient (MCC), respectively. We release the code at https://github.com/BEAM-Labs/CrossBind.Comment: Accepted to AAAI-2

Modeling of System Energy of Rock Under Harmonic Vibro-Impact

Hamiltonian function is proposed and the modeling of system energy of rock under harmonic vibro-impact is undertaken in this study. The modeling includes two aspects, namely, energy equation of rock system with no damping and the one with damping. Also, the results of numerical simulation are presented. Four main control parameters are considered, including natural frequency of rock, impact frequency, impact force, damping coefficient.It is confirmed that the system energy of rock will increase with the increase of natural frequency impact frequency and impact force. While impact force, damping coefficient and stiffness of rock will mainly decide the vibration amplitude of system energy

The Micro Vibration Equation of Rock and Its Analysis in Flat Indenter Basing on the Principle of Least Action

Impact frequency of drill tools, vibration displacement of rock and other factors play a key role on the impact efficiency of vibration and rock breaking effect in the percussion drilling. In this paper, the micro vibration equation of rock in the impact of indenter was established based on the principle of least action. Then the relationship among vibration displacement of rock and quality and natural frequency of rock, impact force and impact frequency of indenter and time were analyzed. The results show that the curve of vibration displacement is kind of shape of cosine function, its size fluctuates up and down in the equilibrium position with the changes in various factors; The greater the impact of flat indenter is, The smaller the quality of rock is, the greater the vibration displacement of rock is; The closer the impact frequency of indenter and natural frequency of rock are, the greater the vibration amplitude of rock is, and it is significantly higher than the situation which the difference of impact frequency of indenter and natural frequency of rock is large