On the Magnetization of the 120∘120^\circ order of the Spin-1/2 Triangular Lattice Heisenberg Model: a DMRG revisit

We revisit the issue about the magnetization of the $120^\circ$ order in the spin-1/2 triangular lattice Heisenberg model (TLHM) with Density Matrix Renormalization Group (DMRG). The accurate determination of the magnetization of this model is challenging for numerical methods and its value exhibits substantial disparities across various methods. We perform a large-scale DMRG calculation of this model by employing bond dimension as large as $D = 24000$ and by studying the system with width as large as $L_\mathrm{y} = 12$. With careful extrapolation with truncation error and suitable finite size scaling, we give a conservative estimation of the magnetization as $M_0 = 0.208(8)$. The ground state energy per site we obtain is $E_g = -0.5503(8)$. Our results provide valuable benchmark values for the development of new methods in the future.Comment: 6 pages, 6 figure

CEO reputation and corporate cash holdings

We investigate whether and to what extent CEO reputation affects both the level and the value of corporate cash holdings for US firms. We show that CEO reputation has a negative impact on the level of corporate cash holdings: the most reputable CEOs hold approximately 17% less cash than the least reputable CEOs. Furthermore, we find that the value of corporate cash holdings held by the most reputable CEOs is much higher than that held by the least reputable CEOs: the difference is approximately 44 cents per dollar for the average firm in our sample. In addition, we also find that the value of one dollar of excess cash holdings held by the most reputable CEOs is worth 77 cents more than that held by the least reputable CEOs. Collectively, our findings provide new evidence in support of prior theories arguing that CEO reputation adds value to the firm’s assets. Meanwhile, our findings also suggest that the agency problem could potentially be mitigated by CEO reputation

PAL: Persona-Augmented Emotional Support Conversation Generation

Due to the lack of human resources for mental health support, there is an increasing demand for employing conversational agents for support. Recent work has demonstrated the effectiveness of dialogue models in providing emotional support. As previous studies have demonstrated that seekers' persona is an important factor for effective support, we investigate whether there are benefits to modeling such information in dialogue models for support. In this paper, our empirical analysis verifies that persona has an important impact on emotional support. Therefore, we propose a framework for dynamically inferring and modeling seekers' persona. We first train a model for inferring the seeker's persona from the conversation history. Accordingly, we propose PAL, a model that leverages persona information and, in conjunction with our strategy-based controllable generation method, provides personalized emotional support. Automatic and manual evaluations demonstrate that PAL achieves state-of-the-art results, outperforming the baselines on the studied benchmark. Our code and data are publicly available at https://github.com/chengjl19/PAL.Comment: Accepted to ACL 2023 finding

Towards Safer Generative Language Models: A Survey on Safety Risks, Evaluations, and Improvements

As generative large model capabilities advance, safety concerns become more pronounced in their outputs. To ensure the sustainable growth of the AI ecosystem, it's imperative to undertake a holistic evaluation and refinement of associated safety risks. This survey presents a framework for safety research pertaining to large models, delineating the landscape of safety risks as well as safety evaluation and improvement methods. We begin by introducing safety issues of wide concern, then delve into safety evaluation methods for large models, encompassing preference-based testing, adversarial attack approaches, issues detection, and other advanced evaluation methods. Additionally, we explore the strategies for enhancing large model safety from training to deployment, highlighting cutting-edge safety approaches for each stage in building large models. Finally, we discuss the core challenges in advancing towards more responsible AI, including the interpretability of safety mechanisms, ongoing safety issues, and robustness against malicious attacks. Through this survey, we aim to provide clear technical guidance for safety researchers and encourage further study on the safety of large models

Role of Mineral Nutrients in Plant-Mediated Synthesis of Three-Dimensional Porous LaCoO3

With the assistance of plant extracts, the facile synthesis of three-dimensional (3D) porous LaCoO3 perovskite is reported at a lower calcination temperature of 500 °C. The formation mechanism is carefully studied by investigating the different roles of organic and inorganic components in Cacumenplatycladi extract. The results indicate that organic components (mainly phenolic acids) function as the similar complex species of citric acid, while the mineral nutrients (Na+, K+, Ca2+, and Mg2+) together with NO3– serve as combustion-aid agents even with trace amounts. Moreover, the biosynthesized LaCoO3 has a high surface area of 32.5 m2 g–1 and exhibits excellent catalytic performance for benzene oxidation. Benzene of 1000 ppm can achieve a stable conversion above 90% at 285 °C in a continuous run for 80 h (weight-hourly space velocity (WHSV) = 40 000 mL g–1 h–1). It can be attributed to the bio-LaCoO3 with more electrophilic adsorption of oxygen species and 3D porous structure

The Emerging of Hydrovoltaic Materials as a Future Technology: A Case Study for China

Water contains tremendous energy in various forms, but very little of this energy has yet been harvested. Nanostructured materials can generate electricity by water-nanomaterial interaction, a phenomenon referred to as hydrovoltaic effect, which potentially extends the technical capability of water energy harvesting. In this chapter, starting by describing the fundamental principle of hydrovoltaic effect, including water-carbon interactions and fundamental mechanisms of harvesting water energy with nanostructured materials, experimental advances in generating electricity from water flows, waves, natural evaporation, and moisture are then reviewed. We further discuss potential applications of hydrovoltaic technologies, analyze main challenges in improving the energy conversion efficiency and scaling up the output power, and suggest prospects for developments of the emerging technology, especially in China

Adaptive variable-grid least-squares reverse-time migration

Variable-grid methods have the potential to save computing costs and memory requirements in forward modeling and least-squares reverse-time migration (LSRTM). However, due to the inherent difficulty of automatic grid discretization, conventional variable-grid methods have not been widely used in industrial production. We propose a variable-grid LSRTM (VG-LSRTM) method based on an adaptive sampling strategy to improve computing efficiency and reduce memory requirements. Based on the mapping relation of two coordinate systems, we derive variable-grid acoustic wave equation and its corresponding Born forward modeling equation. On this basis, we develop a complete VG-LSRTM framework. Numerical experiments on a layered model validate the feasibility of the proposed VG-LSRTM algorithm. LSRTM tests on a modified Marmousi model demonstrate that our method can save computational costs and memory requirements with little accuracy loss

Reconstruction of plant microstructure using distance weighted tessellation algorithm optimized by virtual segmentation

Abstract(#br)The accurate reconstruction model of plant microstructure is important for obtaining the mechanical properties of plant tissues. In this paper, a virtual segmentation technique is proposed to optimize Delaunay triangulation. Based on the optimized Delaunay triangulation, an Optimized Distance Weighted Tessellation (ODWT) algorithm is developed. Two different structures, namely carrot and retting maize vascular bundles, were reconstructed via the ODWT algorithm. The accuracy of ODWT is evaluated statistically by comparing with Centroid-based Voronoi Tessellation (CVT) and Area Weighted Tessellation (AWT). The results show that ODWT has distinct advantages over CVT and AWT. It is worth mentioning that ODWT has better performance than CVT when there exists large diversity in adjacent cell area. It is found that CVT and AWT fail to reconstruct cells with elongated and concave shapes, while ODWT shows excellent feasibility and reliability. Furthermore, ODWT is capable of establishing finite tissue boundary, which CVT and AWT have failed to realize. The purpose of this work is to develop an algorithm with higher accuracy to implement the preprocessing for further numerical study of plants properties. The comparison results of the simulated values of the longitudinal tensile modulus with the experimental value show that ODWT algorithm can improve the prediction accuracy of multi-scale models on mechanical properties

Anisotropic magnetic properties and tunable conductivity in two-dimensional layered NaCrX2 (X=Te,Se,S) single crystals

Monolayer NaCrX2 (X=Te,Se,S) were theoretically proposed to be two-dimensional intrinsic ferromagnetic semiconductors while their physical properties have not been thoroughly investigated in bulk single crystals. We report the single-crystal growth, structural, magnetic and electronic transport properties of NaCr(Te1-xSex)2 (0 6 x 6 1) and NaCrS2. For NaCr(Te1-xSex)2, the strong perpendicular magnetic anisotropy of NaCrTe2 can be gradually tuned to be a nearly isotropic one by Se-doping. Meanwhile, a systematic change in the conductivity with increasing x is observed, displaying a doping-induced metal-insulator-like transition. Under magnetic field larger than 30 koe, both NaCrTe2 and NaCrSe2 can be polarized to a ferromagnetic state. While for NaCrS2, robust antiferromagnetism is observed up to 70 kOe and two field-induced metamagnetic transitions are identified along H||ab. These intriguing properties together with the potential to be exfoliated down to few-layer thickness make NaCrX2 (X=Te,Se,S) promising for exploring spintronic applications