Coronal lines and the importance of deep core-valence correlation in Ag-like ions

We report on large-scale and critically evaluated {\em ab initio} MCDHF calculations of the wavelength of the "coronal", M1 transition $4f\ ^2\mathrm{F}_{5/2}^o-^2\mathrm{F}_{7/2}^o$in Ag-like ions. The transition between these two fine structure levels, which makes up the ground term for$Z \ge 62$in the isoelectronic sequence, has recently been observed in Yb$^{23+}$and W$^{27+}$, where the latter could be of great importance for fusion plasma diagnostics. We present recommended values for all members of the sequence between$Z = 50$and$94$, which are supported by excellent agreement with values from recent experiments. The importance of including core-valence correlation with the$n=3$ shell in the theoretical model is emphasized. The results show close to spectroscopic accuracy for these forbidden lines.Comment: 10 pages, 5 figures, 3 table

Spare support model based on gamma degradation process

Spare parts ordering is very important in the domain of system support based on condition-based maintenance. For a single-unit system with condition monitoring, a joint degradation and spare parts ordering model is established in this paper to achieve the lowest total cost rate as the objective. The degradation process of system is assumed to be followed a gamma process. A decision on optimal spare ordering time by the improved cost rate model based on the proposed degradation model is made. Finally, a case analysis is implemented to demonstrate the effectiveness of the proposed model in this paper. Analysis results show that the proposed model can reduce the cost rate effectively

Biogenesis of iron–sulfur clusters and their role in DNA metabolism

Iron–sulfur (Fe/S) clusters (ISCs) are redox-active protein cofactors that their synthesis, transfer, and insertion into target proteins require many components. Mitochondrial ISC assembly is the foundation of all cellular ISCs in eukaryotic cells. The mitochondrial ISC cooperates with the cytosolic Fe/S protein assembly (CIA) systems to accomplish the cytosolic and nuclear Fe/S clusters maturation. ISCs are needed for diverse cellular functions, including nitrogen fixation, oxidative phosphorylation, mitochondrial respiratory pathways, and ribosome assembly. Recent research advances have confirmed the existence of different ISCs in enzymes that regulate DNA metabolism, including helicases, nucleases, primases, DNA polymerases, and glycosylases. Here we outline the synthesis of mitochondrial, cytosolic and nuclear ISCs and highlight their functions in DNA metabolism

Improving Few-shot and Zero-shot Entity Linking with Coarse-to-Fine Lexicon-based Retriever

Few-shot and zero-shot entity linking focus on the tail and emerging entities, which are more challenging but closer to real-world scenarios. The mainstream method is the ''retrieve and rerank'' two-stage framework. In this paper, we propose a coarse-to-fine lexicon-based retriever to retrieve entity candidates in an effective manner, which operates in two layers. The first layer retrieves coarse-grained candidates by leveraging entity names, while the second layer narrows down the search to fine-grained candidates within the coarse-grained ones. In addition, this second layer utilizes entity descriptions to effectively disambiguate tail or new entities that share names with existing popular entities. Experimental results indicate that our approach can obtain superior performance without requiring extensive finetuning in the retrieval stage. Notably, our approach ranks the 1st in NLPCC 2023 Shared Task 6 on Chinese Few-shot and Zero-shot Entity Linking.Comment: Accepted to NLPCC202

RefGPT: Reference -> Truthful & Customized Dialogues Generation by GPTs and for GPTs

General chat models, like ChatGPT, have attained impressive capability to resolve a wide range of NLP tasks by tuning Large Language Models (LLMs) with high-quality instruction data. However, collecting human-written high-quality data, especially multi-turn dialogues, is expensive and unattainable for most people. Though previous studies have used powerful LLMs to generate the dialogues automatically, but they all suffer from generating untruthful dialogues because of the LLMs hallucination. Therefore, we propose a method called RefGPT to generate enormous truthful and customized dialogues without worrying about factual errors caused by the model hallucination. RefGPT solves the model hallucination in dialogue generation by restricting the LLMs to leverage the given reference instead of reciting their own knowledge to generate dialogues. Additionally, RefGPT adds detailed controls on every utterances to enable highly customization capability, which previous studies have ignored. On the basis of RefGPT, we also propose two high-quality dialogue datasets generated by GPT-4, namely RefGPT-Fact and RefGPT-Code. RefGPT-Fact is 100k multi-turn dialogue datasets based on factual knowledge and RefGPT-Code is 76k multi-turn dialogue dataset covering a wide range of coding scenarios. Our code and datasets are released in https://github.com/ziliwangnlp/RefGP

Automatic Truss Design with Reinforcement Learning

Truss layout design, namely finding a lightweight truss layout satisfying all the physical constraints, is a fundamental problem in the building industry. Generating the optimal layout is a challenging combinatorial optimization problem, which can be extremely expensive to solve by exhaustive search. Directly applying end-to-end reinforcement learning (RL) methods to truss layout design is infeasible either, since only a tiny portion of the entire layout space is valid under the physical constraints, leading to particularly sparse rewards for RL training. In this paper, we develop AutoTruss, a two-stage framework to efficiently generate both lightweight and valid truss layouts. AutoTruss first adopts Monte Carlo tree search to discover a diverse collection of valid layouts. Then RL is applied to iteratively refine the valid solutions. We conduct experiments and ablation studies in popular truss layout design test cases in both 2D and 3D settings. AutoTruss outperforms the best-reported layouts by 25.1% in the most challenging 3D test cases, resulting in the first effective deep-RL-based approach in the truss layout design literature.Comment: IJCAI2023. The codes are available at https://github.com/StigLidu/AutoTrus

CLHA: A Simple yet Effective Contrastive Learning Framework for Human Alignment

Reinforcement learning from human feedback (RLHF) is a crucial technique in aligning large language models (LLMs) with human preferences, ensuring these LLMs behave in beneficial and comprehensible ways to users. However, a longstanding challenge in human alignment techniques based on reinforcement learning lies in their inherent complexity and difficulty in training. To address this challenge, we present a simple yet effective Contrastive Learning Framework for Human Alignment (CLHA) to align LLMs with human preferences directly. CLHA employs a novel rescoring strategy to evaluate the noise within the data by considering its inherent quality and dynamically adjusting the training process. Simultaneously, CLHA utilizes pairwise contrastive loss and adaptive supervised fine-tuning loss to adaptively modify the likelihood of generating responses, ensuring enhanced alignment with human preferences. Using advanced methods, CLHA surpasses other algorithms, showcasing superior performance in terms of reward model scores, automatic evaluations, and human assessments on the widely used ``Helpful and Harmless'' dataset

Environmental contamination characteristics of heavy metals from abandoned lead–zinc mine tailings in China

China holds large-scale lead–zinc mineral resources; however, mining activities often cause severe contamination by heavy metals. This study systemically assessed contamination by eight heavy metals (Cu, Zn, Cd, Pb, Cr, Hg, Ni, and As) in mine tailings, soil, and groundwater from 27 contaminated sites across China. Regarding mine tailings, 1% of the mine tailing samples were hazardous waste and 20% were class II non-hazardous waste. Regarding soil, Zn and Pb showed the highest mean concentrations, at 5574.67 mg/kg and 2034.88 mg/kg, respectively. The indexes of geo-accumulation (Igeo) of eight heavy metals ranged from −3.62 to 7.67, while Zn, Pb, and Cd showed the highest environmental risk levels as the priority pollutants. The contamination levels of these heavy metals in groundwater were generally in the order of Zn>As>Pb>Ni>Cd>Cu>Hg>Cr. In this study, 20% of the soil and 10% of the groundwater samples exceeded the corresponding quality limits. The content of heavy metals in soil, groundwater, and mine tailing were positively correlated, demonstrating the main pollution source and transport paths. The pollution levels of heavy metals in soil and groundwater were listed in the foremost and moderate positions compared with similar sites from other countries, respectively. These results may help determine the pollution levels of lead–zinc mining regions and direct the remediation activities of target sites to support the environmental management of abandoned mining and tailing waste in China