Leveraging Key Information Modeling to Improve Less-Data Constrained News Headline Generation via Duality Fine-Tuning

Recent language generative models are mostly trained on large-scale datasets, while in some real scenarios, the training datasets are often expensive to obtain and would be small-scale. In this paper we investigate the challenging task of less-data constrained generation, especially when the generated news headlines are short yet expected by readers to keep readable and informative simultaneously. We highlight the key information modeling task and propose a novel duality fine-tuning method by formally defining the probabilistic duality constraints between key information prediction and headline generation tasks. The proposed method can capture more information from limited data, build connections between separate tasks, and is suitable for less-data constrained generation tasks. Furthermore, the method can leverage various pre-trained generative regimes, e.g., autoregressive and encoder-decoder models. We conduct extensive experiments to demonstrate that our method is effective and efficient to achieve improved performance in terms of language modeling metric and informativeness correctness metric on two public datasets.Comment: Accepted by AACL-IJCNLP 2022 main conferenc

Experimental investigation of closed built-up sections using four cold-formed steel open sections under axial and eccentric loading

The light gauge steel structure (i.e., cold-formed steel framing) has been widely used in low-rise buildings for its ease of construction and high strength to weight ratio. However, this structural system is limited in member strength and stiffness and inhibits the flexibility of openings for doors and windows and also its use in mid-rise buildings and beyond. Innovation in cold-formed steel moment framing systems is needed. This study proposes a closed built-up section using four cold- formed steel open sections with a high load-bearing capacity that enables the development of high-performance cold-formed steel moment framing systems for mid-rise buildings and beyond. The closed section by combining four open cold-formed steel sections using fasteners can effectively enhance the local and distortional buckling load capacity of the sections under axial loading. Combining with specially designed intersections gusset plate this built-up section offers more potential configurations of beam-column moment connections for cold-formed steel structures. First, a heuristic optimization was performed based on the local and distortional buckling strength using the finite strip method. Second, a test program was developed to investigate the load-bearing capacity of this optimized closed section under axial and eccentric loading. The axial and eccentric loading tests of the built-up closed section column revealed the failure modes of the section under different loading conditions, axial and eccentric in the major-axis and weak-axis, and their load-carrying capacities. The study paved the groundwork for exploring high-performance cold-formed steel moment framing systems with this strong closed built-up section.This work was sponsored by the Natural Science Foundation of Jiangsu Province (BK20191268); and the Project of Central Government for Local Science and Technology Development of Tibetan Autonomous Region (XZ202201YD0032C)

Appliance of plastic hinge method considering distortional buckling in pushover analysis of cold-formed rack structure

The objective of this paper is to develop a yielding surface of thin-walled cold-formed steel members subjected to distortional buckling, and then integrate the surface into pushover analysis of rack structures. Distortional buckling is one of the dominant buckling behaviors of rack members due to their intrinsic section profile. In this study, the Axial-Moment-Moment (PMM) interaction surface for a perforated omega column is established using the finite element method and compared with the theoretical one by EN 15512. It is found that the theoretical PMM domain might be conservative. Then, pushover analyses using these two PMM surfaces along with PMM from ASCE 7 are performed on a cold-formed steel rack. The pushover curve and failure mechanism of the models are analyzed with those from a detailed shell Finite Element model and a full-scale experiment. Finally, this approach of employing distortional PMM is comprehensively assessed from computational cost and reliability for its efficiency in engineering practice.We are grateful to Natural Science Foundation of Jiangsu Province for their financial support (No: BK20191268) to this paper

Early Warning System for Load Distribution in Automated Warehouse Based on Seismic Safety

As an integral part of the storage system in automated warehouse, the structural behaviors of steel rack structures have been extensively studied. However, little research has been conducted on the seismic performance evaluation of racks under different load distributions and also a warning system for safety evaluation of the load distribution that might cause unfavorable seismic performance. The objective of this study is to develop a method of evaluating seismic safety and an early warning system of over-limit load distribution for racks with spine bracings. The genetic algorithm was employed to seek and identify the influence of load distribution on the seismic performance of racks with spine bracing. Then, a formula for safety evaluation for racks with spine bracing was derived and its reliability was validated. An early warning system for over-limit load distribution was established and codified in a software package. Different safety statuses using a color system like Green, Red, and Yellow were employed in the software package as an indicator of the load distribution level of racks. Finally, the system developed was applied to the actual racks in an automated warehouse in Nanjing to demonstrate its applicability and reliability.This work was sponsored by the Natural Science Foundation of Jiangsu Province (BK20191268); and the Project of Central Government for Local Science and Technology Development of Tibetan Autonomous Region (XZ202201YD0032C)

Knowledge spillover, knowledge management capabilities, and innovation among returnee entrepreneurial firms in emerging markets: Does entrepreneurial ecosystem matter?

The paper brings an entrepreneurial ecosystem approach to examine the conditions under which returnee entrepreneurs can overcome their liabilities and promote innovation in emerging markets. The existing literature has focused on how returnee entrepreneurial firms can transit knowledge to local firms with the assumption that the former are more innovative than the latter. However, returnee entrepreneurial firms themselves experience difficulties in achieving superior innovation performance as they face liabilities when returning to their home countries. In this paper, we argue that such firms can take advantage of the knowledge spillover in the entrepreneurial ecosystem to promote innovation performance by enhancing their own knowledge management capability. The empirical evidence supports this proposition. Although we proposed that this relationship is likely contingent upon the attributes of entrepreneurial ecosystem, empirical evidence does not support it. Theoretical and practical implications are discussed

Seismic performance and most unfavorable and favorable Load distributions of steel storage rack: an optimization approach

In the current rack seismic design, the load distribution is generally considered to be placed uniformly on the rack, but the reality usually differ. In this paper, the objective is to identify the most unfavorable and favorable load distribution of the braced and unbraced racks under seismic loading through a stochastic optimization - Genetic Algorithm (GA). The GA optimization is performed with an established computational models of racks and the pushover analysis is integrated to evaluate seismic performance of the racks. It is analyzed that the distribution of load has a great influence on the seismic performance of steel racks. During the optimization, including the optimized solutions, there are other loading distributions that will make the racks fail with the seismic requirements. Statistical summary of these load pattern results create a cloud map. The cloud map from the optimization results show that the most unfavorable load distribution is in a ‘凸’ shape of the 3D space of the racks and the safe load distribution holds a ‘凹’ shape for braced racks. Meanwhile, unbracing racks have the characteristics of an unfavorable load distribution of a ‘卩’ shape. The gravity center of the loading has an apparent impact on the braced rack’s seismic performance such as the number of load carried by the columns in the back pulling zone, the total horizontal seismic force, and the distribution of local at the dangerous position. On the other hand, no obvious impact of the gravity.We are grateful to Natural Science Foundation of Jiangsu Province for their financial support(No: BK20191268) to this paper

Genome sequences reveal global dispersal routes and suggest convergent genetic adaptations in seahorse evolution

Seahorses have a circum-global distribution in tropical to temperate coastal waters. Yet, seahorses show many adaptations for a sedentary, cryptic lifestyle: they require specific habitats, such as seagrass, kelp or coral reefs, lack pelvic and caudal fins, and give birth to directly developed offspring without pronounced pelagic larval stage, rendering long-range dispersal by conventional means inefficient. Here we investigate seahorses’ worldwide dispersal and biogeographic patterns based on a de novo genome assembly of Hippocampus erectus as well as 358 re-sequenced genomes from 21 species. Seahorses evolved in the late Oligocene and subsequent circum-global colonization routes are identified and linked to changing dynamics in ocean currents and paleo-temporal seaway openings. Furthermore, the genetic basis of the recurring “bony spines” adaptive phenotype is linked to independent substitutions in a key developmental gene. Analyses thus suggest that rafting via ocean currents compensates for poor dispersal and rapid adaptation facilitates colonizing new habitats.Fil: Chunyan, Li. Southern Marine Science and Engineering Guangdong Laboratory; China. Pilot National Laboratory for Marine Science and Technology; China. Chinese Academy of Sciences; República de ChinaFil: Olave, Melisa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Provincia de Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Universidad Nacional de Cuyo. Instituto Argentino de Investigaciones de las Zonas Áridas; Argentina. University of Konstanz; AlemaniaFil: Hou, Yali. Chinese Academy of Sciences; República de ChinaFil: Geng, Qi. Chinese Academy of Sciences; República de China. Southern Marine Science and Engineering Guangdong Laboratory; ChinaFil: Schneider, Ralf. University Of Konstanz; Alemania. Helmholtz Centre for Ocean Research Kie; AlemaniaFil: Zeixa, Gao. Huazhong Agricultural University; ChinaFil: Xiaolong, Tu. Allwegene Technologies ; ChinaFil: Xin, Wang. Chinese Academy of Sciences; República de ChinaFil: Furong, Qi. China National Center for Bioinformation; China. University of Chinese Academy of Sciences; ChinaFil: Nater, Alexander. University of Konstanz; AlemaniaFil: Kautt, Andreas F.. University of Konstanz; Alemania. Harvard University; Estados UnidosFil: Wan, Shiming. Chinese Academy of Sciences; República de ChinaFil: Yanhong, Zhang. Chinese Academy of Sciences; República de ChinaFil: Yali, Liu. Chinese Academy of Sciences; República de ChinaFil: Huixian, Zhang. Chinese Academy of Sciences; República de ChinaFil: Bo, Zhang. Chinese Academy of Sciences; República de ChinaFil: Hao, Zhang. Chinese Academy of Sciences; República de ChinaFil: Meng, Qu ,. Chinese Academy of Sciences; República de ChinaFil: Shuaishuai, Liu. Chinese Academy of Sciences; República de ChinaFil: Zeyu, Chen. Chinese Academy of Sciences; República de China. University of Chinese Academy of Sciences; ChinaFil: Zhong, Jia. Chinese Academy of Sciences; República de ChinaFil: Zhang, He. BGI-Shenzhen; ChinaFil: Meng, Lingfeng. BGI-Shenzhen; ChinaFil: Wang, Kai. Ludong University; ChinaFil: Yin, Jianping. Chinese Academy of Sciences; República de ChinaFil: Huang, Liangmin. Chinese Academy of Sciences; República de China. University of Chinese Academy of Sciences; ChinaFil: Venkatesh, Byrappa. Institute of Molecular and Cell Biology; SingapurFil: Meyer, Axel. University of Konstanz; AlemaniaFil: Lu, Xuemei. Chinese Academy of Sciences; República de ChinaFil: Lin, Qiang. Chinese Academy of Sciences; República de China. Southern Marine Science and Engineering Guangdong Laboratory; China. Pilot National Laboratory for Marine Science and Technology; China. University of Chinese Academy of Sciences; Chin