Learning to Imagine: Visually-Augmented Natural Language Generation

People often imagine relevant scenes to aid in the writing process. In this work, we aim to utilize visual information for composition in the same manner as humans. We propose a method, LIVE, that makes pre-trained language models (PLMs) Learn to Imagine for Visuallyaugmented natural language gEneration. First, we imagine the scene based on the text: we use a diffusion model to synthesize high-quality images conditioned on the input texts. Second, we use CLIP to determine whether the text can evoke the imagination in a posterior way. Finally, our imagination is dynamic, and we conduct synthesis for each sentence rather than generate only one image for an entire paragraph. Technically, we propose a novel plug-and-play fusion layer to obtain visually-augmented representations for each text. Our vision-text fusion layer is compatible with Transformerbased architecture. We have conducted extensive experiments on four generation tasks using BART and T5, and the automatic results and human evaluation demonstrate the effectiveness of our proposed method. We will release the code, model, and data at the link: https://github.com/RUCAIBox/LIVE.Comment: Accepted by ACL 202

Recent Advances in RecBole: Extensions with more Practical Considerations

RecBole has recently attracted increasing attention from the research community. As the increase of the number of users, we have received a number of suggestions and update requests. This motivates us to make some significant improvements on our library, so as to meet the user requirements and contribute to the research community. In order to show the recent update in RecBole, we write this technical report to introduce our latest improvements on RecBole. In general, we focus on the flexibility and efficiency of RecBole in the past few months. More specifically, we have four development targets: (1) more flexible data processing, (2) more efficient model training, (3) more reproducible configurations, and (4) more comprehensive user documentation. Readers can download the above updates at: https://github.com/RUCAIBox/RecBole.Comment: 5 pages, 3 figures, 3 table

Magnetic Manganese Oxide Sweetgum-Ball Nanospheres with Large Mesopores Regulate Tumor Microenvironments for Enhanced Tumor Nanotheranostics.

An important objective of cancer nanomedicine is to improve the delivery efficacy of functional agents to solid tumors for effective cancer imaging and therapy. Stimulus-responsive nanoplatforms can target and regulate the tumor microenvironment (TME) for the optimization of cancer theranostics. Here, we developed magnetic manganese oxide sweetgum-ball nanospheres (MMOSs) with large mesopores as tools for improved cancer theranostics. MMOSs contain magnetic iron oxide nanoparticles and mesoporous manganese oxide (MnO2) nanosheets, which are assembled into gumball-like structures on magnetic iron oxides. The large mesopores of MMOSs are suited for cargo loading with chlorin e6 (Ce6) and doxorubicin (DOX), thus producing so-called CD@MMOSs. The core of magnetic iron oxides could achieve magnetic targeting of tumors under a magnetic field (0.25 mT), and the targeted CD@MMOSs may decompose under TME conditions, thereby releasing loaded cargo molecules and reacting with endogenous hydrogen peroxide (H2O2) to generate oxygen (O2) and manganese (II) ions (Mn2+). Investigation in vivo in tumor-bearing mice models showed that the CD@MMOS nanoplatforms achieved TME-responsive cargo release, which might be applied in chemotherapy and photodynamic therapy. A remarkable in vivo synergy of diagnostic and therapeutic functionalities was achieved by the decomposition of CD@MMOSs and coadministration with chemo-photodynamic therapy of tumors using the magnetic targeting mechanism. Thus, the result of this study demonstrates the feasibility of smart nanotheranostics to achieve tumor-specific enhanced combination therapy

A Survey of Large Language Models

Language is essentially a complex, intricate system of human expressions governed by grammatical rules. It poses a significant challenge to develop capable AI algorithms for comprehending and grasping a language. As a major approach, language modeling has been widely studied for language understanding and generation in the past two decades, evolving from statistical language models to neural language models. Recently, pre-trained language models (PLMs) have been proposed by pre-training Transformer models over large-scale corpora, showing strong capabilities in solving various NLP tasks. Since researchers have found that model scaling can lead to performance improvement, they further study the scaling effect by increasing the model size to an even larger size. Interestingly, when the parameter scale exceeds a certain level, these enlarged language models not only achieve a significant performance improvement but also show some special abilities that are not present in small-scale language models. To discriminate the difference in parameter scale, the research community has coined the term large language models (LLM) for the PLMs of significant size. Recently, the research on LLMs has been largely advanced by both academia and industry, and a remarkable progress is the launch of ChatGPT, which has attracted widespread attention from society. The technical evolution of LLMs has been making an important impact on the entire AI community, which would revolutionize the way how we develop and use AI algorithms. In this survey, we review the recent advances of LLMs by introducing the background, key findings, and mainstream techniques. In particular, we focus on four major aspects of LLMs, namely pre-training, adaptation tuning, utilization, and capacity evaluation. Besides, we also summarize the available resources for developing LLMs and discuss the remaining issues for future directions.Comment: ongoing work; 51 page

The Pathology of Poliomyelitis and the Vaccines and Nonvaccine Therapy

Poliomyelitis is an exclusively human disease that mainly affects children. Clinical features of poliomyelitis can be varied, from mild illness to the most severe paralysis, and the factor why poliomyelitis has different performances in individuals has been proved strongly correlated with membrane protein CD155. The nervous system shows a special protecting phenomenon against the invasion of poliovirus, and the mechanism is not very clear at present. Vaccines are the main means of preventing and controlling polio, and many different vaccines have been invented in the process of fighting polio. Inactivated polio vaccine (IPV) and oral polio vaccine (OPV) are the two main vaccines. IPV is known for its safety while OPV is widely used in developing countries because of its relatively low cost. This usage also leads to some side effects: vaccine-associated paralytic polio (VAPP) and vaccine-derived poliovirus (VDPV). Now, for polio eradication, the elimination of these two diseases has become particularly important. Thus, a new type of vaccine was created: sequential IPV-OPV with the safety of IPV and the low cost of OPV. This paper will talk about the different polio vaccines and their effects. An enormous difference between people who have gotten the vaccine and people who have not got the vaccine. Comparing the two kinds of people, people who get normal poliovirus, and people who get poliovirus after taking a vaccine, known as VAPP (vaccine-associated paralytic poliomyelitis), the former cannot get full recovery whole life and the latter has a very low possibility. In conclusion, people should take vaccines if it is affordable for them

Profound Impact of Economic Openness and Digital Economy towards a Sustainable Development: A New Look at RCEP Economies

Sustainable development has become a serious challenge for the globe. Therefore, globalization and the digital economy are considered crucial factors for sustainable development (SD). The current study tries to estimate the link between trade openness and information and communication technology (ICT) with sustainable growth via a linear function in which economic growth, urbanization, and human capital are taken as independent variables. The study employs the Interactive Fixed Effect (IFE) and Dynamic Common Correlated Effect (D-CCE) to quantify the long-term association among variables in a multiplicative framework. The obtained outcomes show a significant contribution of globalization and the digital economy to sustainable growth. Likewise, economic growth and human capital cause a decline in sustainable growth. Moreover, the empirical outcomes show the discouraging role of urbanization in sustainable development. Additionally, a bi-directional association exists between sustainable development and trade openness and economic growth, trade openness and economic growth, urbanization and human capital, and economic growth and urbanization. Such findings further strengthen policymakers’ belief in other nations to promote sustainable development. Moreover, to alleviate the economic growth losses, we suggest setting up a sustainable development sharing mechanism among regions

Profound Impact of Economic Openness and Digital Economy towards a Sustainable Development: A New Look at RCEP Economies

Sustainable development has become a serious challenge for the globe. Therefore, globalization and the digital economy are considered crucial factors for sustainable development (SD). The current study tries to estimate the link between trade openness and information and communication technology (ICT) with sustainable growth via a linear function in which economic growth, urbanization, and human capital are taken as independent variables. The study employs the Interactive Fixed Effect (IFE) and Dynamic Common Correlated Effect (D-CCE) to quantify the long-term association among variables in a multiplicative framework. The obtained outcomes show a significant contribution of globalization and the digital economy to sustainable growth. Likewise, economic growth and human capital cause a decline in sustainable growth. Moreover, the empirical outcomes show the discouraging role of urbanization in sustainable development. Additionally, a bi-directional association exists between sustainable development and trade openness and economic growth, trade openness and economic growth, urbanization and human capital, and economic growth and urbanization. Such findings further strengthen policymakers’ belief in other nations to promote sustainable development. Moreover, to alleviate the economic growth losses, we suggest setting up a sustainable development sharing mechanism among regions

The Research of Mathematical Method and Position Control of Actuator in Power Switchgear

Transient effects such as overvoltage and inrush currents will be caused due to opening and closing the switchgear at random phase. Phase-controlled technology present in recent years, which is restricted by the operation dispersion of actuator, can limit the transient effects. And the dispersion of the switchgear with a permanent magnetic actuator (PMA) is small. Therefore, the research of mathematical method and position control in this paper is based on the PMA. Firstly, the dynamic mathematical method and simulation system established in MATLAB are used to improve the design of the PMA owing same type. Secondly, simulation with the use of improved fuzzy algorithm is carried out. And an optimized self-adaptive fuzzy algorithm is obtained in the simulation process which can be used to trace the given displacement curve. Finally, a large number of tracing experiments have been done on the 35 kV breaker prototype to verify the effectiveness of the algorithm. In the experiments, the closing time of breaker can be stabilized within ±0.5 ms when capacitor voltage and capacitance change. These results prove that the mathematical model and the fuzzy algorithm are effective and practical

Spatial Distribution and Ten Years Change of Global Built-up Areas Derived from GlobeLand30

As an important anthropogenic indicator and human ecological foot print,built-up areas and its change is an essential information for environmental change analysis, geo-conditional monitoring and sustainable development. In the past, built-up areas and its change studies were mainly focused on a city, regional or nation scale, and it has not been possible to conduct a global built-up areas and its change analysis yet. This paper presented the methodology and results of the first global analysis of built-up areas and its ten year's change(2000-2010) using GlobeLand30, China's 30 meter resolution global land cover data sets-. Built-up areas, change rate and increase proportion were the major statistical variables used for the statistical analysis. The result shows that the total area of the global built-up areas is 1.1875 million km2, covering 0.88% of the total area of the global land surface; the area of global built-up areas increased 57400km2 with the variation rate of 5.08% from 2000 to 2010;and China and United Sates are the top two countries having the largest increased built-up areas, i.e., accounting over 50% of that of the global total; 50.26% of the total increased built-up areas comes from the arable land. These results provide reliable spatio-temporal information to the study of human domination of Earth's ecosystems and global monitoring