Graph ODE with Factorized Prototypes for Modeling Complicated Interacting Dynamics

This paper studies the problem of modeling interacting dynamical systems, which is critical for understanding physical dynamics and biological processes. Recent research predominantly uses geometric graphs to represent these interactions, which are then captured by powerful graph neural networks (GNNs). However, predicting interacting dynamics in challenging scenarios such as out-of-distribution shift and complicated underlying rules remains unsolved. In this paper, we propose a new approach named Graph ODE with factorized prototypes (GOAT) to address the problem. The core of GOAT is to incorporate factorized prototypes from contextual knowledge into a continuous graph ODE framework. Specifically, GOAT employs representation disentanglement and system parameters to extract both object-level and system-level contexts from historical trajectories, which allows us to explicitly model their independent influence and thus enhances the generalization capability under system changes. Then, we integrate these disentangled latent representations into a graph ODE model, which determines a combination of various interacting prototypes for enhanced model expressivity. The entire model is optimized using an end-to-end variational inference framework to maximize the likelihood. Extensive experiments in both in-distribution and out-of-distribution settings validate the superiority of GOAT

An atlas of DNA methylomes in porcine adipose and muscle tissues

It is evident that epigenetic factors, especially DNA methylation, have essential roles in obesity development. Here, using pig as a model, we investigate the systematic association between DNA methylation and obesity. We sample eight variant adipose and two distinct skeletal muscle tissues from three pig breeds living within comparable environments but displaying distinct fat level. We generate 1,381 Gb of sequence data from 180 methylated DNA immunoprecipitation libraries, and provide a genome-wide DNA methylation map as well as a gene expression map for adipose and muscle studies. The analysis shows global similarity and difference among breeds, sexes and anatomic locations, and identifies the differentially methylated regions. The differentially methylated regions in promoters are highly associated with obesity development via expression repression of both known obesity-related genes and novel genes. This comprehensive map provides a solid basis for exploring epigenetic mechanisms of adipose deposition and muscle growth

Solvothermal Synthesis and Characterization of Chalcopyrite CuInSe2 Nanoparticles

The ternary I-III-VI2 semiconductor of CuInSe2 nanoparticles with controllable size was synthesized via a simple solvothermal method by the reaction of elemental selenium powder and CuCl as well as InCl3 directly in the presence of anhydrous ethylenediamine as solvent. X-ray diffraction patterns and scanning electron microscopy characterization confirmed that CuInSe2 nanoparticles with high purity were obtained at different temperatures by varying solvothermal time, and the optimal temperature for preparing CuInSe2 nanoparticles was found to be between 180 and 220 °C. Indium selenide was detected as the intermediate state at the initial stage during the formation of pure ternary compound, and the formation of copper-related binary phase was completely deterred in that the more stable complex [Cu(C2H8N2)2]+ was produced by the strong N-chelation of ethylenediamine with Cu+. These CuInSe2 nanoparticles possess a band gap of 1.05 eV calculated from UV–vis spectrum, and maybe can be applicable to the solar cell devices

Attitudes on the donation of human embryos for stem cell research among Chinese IVF patients and students

Bioethical debates on the use of human embryos and oocytes for stem cell research have often been criticized for the lack of empirical insights into the perceptions and experiences of the women and couples who are asked to donate these tissues in the IVF clinic. Empirical studies that have investigated the attitudes of IVF patients and citizens on the (potential) donation of their embryos and oocytes have been scarce and have focused predominantly on the situation in Europe and Australia. This article examines the viewpoints on the donation of embryos for stem cell research among IVF patients and students in China. Research into the perceptions of patients is based on in-depth interviews with IVF patients and IVF clinicians. Research into the attitudes of students is based on a quantitative survey study (n=427). The empirical findings in this paper indicate that perceptions of the donation of human embryos for stem cell research in China are far more diverse and complex than has commonly been suggested. Claims that ethical concerns regarding the donation and use of embryos and oocytes for stem cell research are typical for Western societies but absent in China cannot be upheld. The article shows that research into the situated perceptions and cultural specificities of human tissue donation can play a crucial role in the deconstruction of politicized bioethical argumentation and the (often ill-informed) assumptions about “others” that underlie socio-ethical debates on the moral dilemmas of technology developments in the life sciences

Artificial intelligence : A powerful paradigm for scientific research

Y Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day life. The ML techniques have been developed to analyze high-throughput data with a view to obtaining useful insights, categorizing, predicting, and making evidence-based decisions in novel ways, which will promote the growth of novel applications and fuel the sustainable booming of AI. This paper undertakes a comprehensive survey on the development and application of AI in different aspects of fundamental sciences, including information science, mathematics, medical science, materials science, geoscience, life science, physics, and chemistry. The challenges that each discipline of science meets, and the potentials of AI techniques to handle these challenges, are discussed in detail. Moreover, we shed light on new research trends entailing the integration of AI into each scientific discipline. The aim of this paper is to provide a broad research guideline on fundamental sciences with potential infusion of AI, to help motivate researchers to deeply understand the state-of-the-art applications of AI-based fundamental sciences, and thereby to help promote the continuous development of these fundamental sciences.Peer reviewe

Correlated Data Routing in Sensor Networks

We study the correlated information routing with source coding using explicit side information in wireless sensor networks. This problem belongs to the difficult joint compression/routing optimization, and has its connections to the network information theory. We present our network and rate models based on explicit side information available at both the encoder and decoder, then introduce the integer programming formulation with a few simplifying assumptions. A two-stage DPCM coding scheme that can take advantage of the explicit side information and report the additional spatial is also included

Detection Fidelity in Distributed Wireless Sensor Neworks

This paper discusses the sensing, quantization, and interpolation errors in distributed sensor networks

Detection Fidelity in Distributed Wireless Sensor Neworks

This paper discusses the sensing, quantization, and interpolation errors in distributed sensor networks