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Within the electronic design automation (EDA) domain, artificial intelligence (AI)-driven solutions have emerged as formidable tools, yet they typically augment rather than redefine existing methodologies. These solutions often repurpose deep learning models from other domains, such as vision, text, and graph analytics, applying them to circuit design without tailoring to the unique complexities of electronic circuits. Such an “AI4EDA” approach falls short of achieving a holistic design synthesis and understanding, overlooking the intricate interplay of electrical, logical, and physical facets of circuit data. This study argues for a paradigm shift from AI4EDA towards AI-rooted EDA from the ground up, integrating AI at the core of the design process. Pivotal to this vision is the development of a multimodal circuit representation learning technique, poised to provide a comprehensive understanding by harmonizing and extracting insights from varied data sources, such as functional specifications, register-transfer level (RTL) designs, circuit netlists, and physical layouts. We champion the creation of large circuit models (LCMs) that are inherently multimodal, crafted to decode and express the rich semantics and structures of circuit data, thus fostering more resilient, efficient, and inventive design methodologies. Embracing this AI-rooted philosophy, we foresee a trajectory that transcends the current innovation plateau in EDA, igniting a profound “shift-left” in electronic design methodology. The envisioned advancements herald not just an evolution of existing EDA tools but a revolution, giving rise to novel instruments of design-tools that promise to radically enhance design productivity and inaugurate a new epoch where the optimization of circuit performance, power, and area (PPA) is achieved not incrementally, but through leaps that redefine the benchmarks of electronic systems’ capabilities. [ABSTRACT FROM AUTHOR]

Increased soil salinization is among the main factors that limits safe rice production. Arbuscular mycorrhizal fungi (AMF) have been shown to alleviate the toxic effects of salt stress in plants. However, more studies on AMF combined with other functional microorganisms are needed to further improve salt tolerance in rice. Therefore, the compound inoculum Funneliformis mosseae (Fm) together with two functional microorganisms, Piriformospora indica (Pi) and Agrobacterium rhizogenes (Ar) was evaluated for their effect on the rice growth, photosynthetic gas exchange parameters, ion homeostasis, and the expression of salt tolerance-related genes under 0, 80, 120 and 160 mM salt stress conditions. The results showed that: (1) the rice seedling biomass of the AMF compound inoculant treatment group was significantly higher than that of the non-inoculation treatment group (P < 0.05); (2) under NaCl stress, inoculation with AMF compound inoculants can activate the rice antioxidant enzyme system and improve osmoregulation ability; (3) AMF compound inoculants can increase the concentration of K+ in the plant and inhibit the transfer of Na+ to rice leaves, maintaining a high K+/Na+; and (4) AMF compound inoculants could induce and regulate the overexpression of genes related to salt tolerance, photosynthesis and ion homeostasis in rice, and improve the tolerance of rice under salt stress. Our study showed that AMF compound inoculants could improve the adaptability of rice under NaCl stress and promote plant growth by regulating the photosynthetic gas exchange parameter, reactive oxygen species (ROS) scavenging ability, and ion homeostasis of plants. These results suggest that AMF compound inoculants may play an important role in improving rice productivity in salinized soil. [ABSTRACT FROM AUTHOR]

In vehicular environment, Location Based Services (LBS) are widely deployed to provide a service or a piece of information that is related to the location of a driver. Though a series of technologies, such as anonymity, mix zone or private information retrieval, can be exploited to protect the drivers position information, the data proprietorship is always ignored. In addition, since the embedded systems like Onboard Unit are generally recourse-constrained, efficient schemes are urgent for now. In this paper, we presented a novel oblivious transfer protocol based on Number Theory Research Unit Encryption and structured a security LBS scheme in terms of it. Comparing with Jannati and Bahrak's protocol, it is concluded that our scheme is more efficient and practical. [ABSTRACT FROM AUTHOR]