Winkler model for dynamic response of composite caisson-piles foundations: Lateral response

As the first part of a sequence focusing on the dynamic response of composite caisson-piles foundations (CCPFs1), this paper develops a simplified method for the lateral response of these foundations. A Winkler model for the lateral vibration of the CCPF is created by joining the two components, the caisson and the pile group, where the four-spring Winkler model is utilized for the caisson and axial-lateral coupled vibration equations are derived for the pile group. For determining the coefficients of the four-spring Winkler model for the caissons, embedded footing impedance is used and a modification on the rotational embedment factor is made for the sake of the geometrical difference between shallow footings and caissons. Comparisons against results from finite element simulations demonstrate the reliability of this modified four-spring Winkler model for caissons in both homogenous and layered soils. The proposed simplified method for the lateral vibration of CCPFs is verified also by 3D finite element modeling. Finally, through an example, the idea of adding piles beneath the caisson is proved to be of great significance to enhance the resistance of the foundation against lateral dynamic loads

CPET: Effective Parameter-Efficient Tuning for Compressed Large Language Models

Parameter-efficient tuning (PET) has been widely explored in recent years because it tunes much fewer parameters (PET modules) than full-parameter fine-tuning (FT) while still stimulating sufficient knowledge from large language models (LLMs) for downstream tasks. Moreover, when PET is employed to serve multiple tasks, different task-specific PET modules can be built on a frozen LLM, avoiding redundant LLM deployments. Although PET significantly reduces the cost of tuning and deploying LLMs, its inference still suffers from the computational bottleneck of LLMs. To address the above issue, we propose an effective PET framework based on compressed LLMs, named "CPET". In CPET, we evaluate the impact of mainstream LLM compression techniques on PET performance and then introduce knowledge inheritance and recovery strategies to restore the knowledge loss caused by these compression techniques. Our experimental results demonstrate that, owing to the restoring strategies of CPET, collaborating task-specific PET modules with a compressed LLM can achieve comparable performance to collaborating PET modules with the original version of the compressed LLM and outperform directly applying vanilla PET methods to the compressed LLM

An Extensible Plug-and-Play Method for Multi-Aspect Controllable Text Generation

Recently, multi-aspect controllable text generation that controls the generated text in multiple aspects (e.g., sentiment, topic, and keywords) has attracted increasing attention. Although methods based on parameter efficient tuning like prefix-tuning could achieve multi-aspect controlling in a plug-and-play way, the mutual interference of multiple prefixes leads to significant degeneration of constraints and limits their extensibility to training-time unseen aspect combinations. In this work, we provide a theoretical lower bound for the interference and empirically found that the interference grows with the number of layers where prefixes are inserted. Based on these analyses, we propose using trainable gates to normalize the intervention of prefixes to restrain the growing interference. As a result, controlling training-time unseen combinations of aspects can be realized by simply concatenating corresponding plugins such that new constraints can be extended at a lower cost. In addition, we propose a unified way to process both categorical and free-form constraints. Experiments on text generation and machine translation demonstrate the superiority of our approach over baselines on constraint accuracy, text quality, and extensibility.Comment: long paper, accepted by ACL 2023 (main conference

Soil cover improves soil quality in a young walnut forest in the Sichuan Basin, China

The soil quality index (SQI) is based on several key indicators and is used to assess soil quality. More than 250,000 ha of walnut saplings (Juglans regia L.) were planted in previous cropland areas in the Sichuan Basin, China, using a range of soil cover types that may affect soil quality with effects that are unclear. We investigated the effects of white film (WF), black film (BF), shade netting (SN), and maize straw (MS) soil cover types and an uncovered control type (CK) on soil chemical and biological indicators and the SQI in the 0-15 cm soil layer in a young walnut forest in the Sichuan Basin over a 27-month study period. The results showed that all soil cover types increased the soil organic matter (SOM), total potassium (TK), and available potassium (AK) concentrations (p < 0.05), whereas the total nitrogen (TN) and available nitrogen (AN) concentrations were greater only in soils covered by MS than in CK (p < 0.05). The available phosphorus concentrations were 64.1 and 193.2% greater in soils covered by BF and MS treatments, respectively, than in the CK (p < 0.05). The numbers of soil faunal groups (N) were 45.7, 36.4, 37.2, and 101.5% higher in WF, BF, SN, and MS, respectively, than in CK (p < 0.05); the individual numbers (S) were 92.3, 36.2, 100.8, and 154.5% greater in WF, BF, SN, and MS, respectively, than in CK (p < 0.05). The microbial biomass carbon (MBC) was 15.5, 32.3, 45.0, and 77.1% greater in WF, BF, SN, and MS than in CK, respectively (p < 0.05). Redundancy discriminant analysis revealed strong positive interactions between biological indicators (MBC, N, and S) and SOM, AN, and AK concentrations. SOM, TN, AK, S, and MBC were the minimum required variables for the effective assessment of the SQI. All four soil cover types led to an improved SQI (p < 0.05), and MS had the greatest effect on SOM, TN, AN, AP, N, S, MBC, and SQI (p < 0.05). In conclusion, all four soil cover types increased the SOM levels, TK, AK, and MBC concentrations, soil faunal diversity, and SQI. The MS treatment was the most cost-effective and efficient measure to improve soil fertility, ecological function, and overall soil quality in the studied walnut forest