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

reuse strategies in distributed complex event detection

Software Engineering Society of Korean; Institute for Information Scientists and Engineers; IEEE Reliability Society; KAIST (Korea Advanced Institute of Science and Technology); Korea Information Promotion Agency; Samsung SDSIn a Pub/Sub system, the procedure of distributed event detection can be divided into two interacting phases: the subscription matching and the subscription/ event routing. Also, the performance of the system is greatly influenced by these two parts. Adopting a reuse strategy in matching and routing can reduce matching workload and network traffic. However, few of the existing researches provide a reuse solution comprehensively in distributed environments. This paper focuses on exploiting reuse to improve distributed complex event detection. The Pub/Sub system OGENS is introduced, in which the reuses are exploited in the channel-based subscription/event routing and the complex event matching. © 2009 IEEE

Use of Carbon Nanoparticles to Improve Soil Fertility, Crop Growth and Nutrient Uptake by Corn (Zea mays L.)

The use of carbon nanoparticles (CNPs) as a fertilizer synergist to enhance crop growth has attracted increasing interest. However, current understanding about plant growth and soil response to CNPs is limited. In the present study, we investigated the effects of CNPs at different application rates on soil properties, the plant growth and nutrient use efficiency (NUE) of corn (Zea mays L.) in two agricultural soils (Spodosol and Alfisol). The results showed that CNPs affected corn growth in a dose-dependent manner, augmenting and retarding growth at low and at high concentrations, respectively. The amendment at the optimal rate of 200 mg CNPs kg−1 significantly enhanced corn growth as indicated by improved plant height, biomass yield, nutrient uptake and nutrient use efficiency, which could be explained by the higher availability of phosphorus and nitrogen in the amended soils. The application of CNPs largely stimulated soil urease activity irrespectively of soil types. However, the responses of dehydrogenase and phosphatase to CNPs were dose dependent; their activity significantly increased with the increasing application rates of CNPs up to 200 mg kg−1 but declined at higher rates (>400 mg kg−1). These findings have important implications in the field application of CNPs for enhancing nutrient use efficiency and crop production in tropical/subtropical regions

Density-Controlled Metal Nanocluster with Modulated Surface for pH-Universal and Robust Water Splitting

Copyright © 1999-2023 John Wiley & Sons, Inc. All rights reserved. Reducing the particle sizes of transition metals (TMs) and avoiding their aggregation are crucial for increasing the TMs atom utilization and enhancing their industrial potential. However, it is still challenging to achieve uniform distributed and density-controlled TMs nanoclusters (NCs) under high temperatures due to the strong interatomic metallic bonds and high surface energy of NCs. Herein, a series of TMs NCs with controllable density and nitrogen-modulated surface are prepared with the assistance of a selected covalent organic polymer (COP), which can provide continuous anchoring sites and size-limited skeletons. The prepared Ir NCs show superior hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) activities than commercial Pt/C and Ir/C in both acid and alkaline media. In particular, the as-prepared Ir NCs exhibit remarkable full water splitting performance, reaching a current density of 10 mA cm(-2) at ultralow overpotentials of 1.42 and 1.43 V in alkaline and acidic electrolyte, respectively. The excellent electrocatalytic activities are attributed to the increased surface atom utilization and the improved intrinsic activity of Ir NCs. More importantly, the Ir NCs catalyst shows superior long-term stability due to the strong interaction between Ir NCs and the N-doped carbon layer.11Nsciescopu