ReactIE: Enhancing Chemical Reaction Extraction with Weak Supervision

Structured chemical reaction information plays a vital role for chemists engaged in laboratory work and advanced endeavors such as computer-aided drug design. Despite the importance of extracting structured reactions from scientific literature, data annotation for this purpose is cost-prohibitive due to the significant labor required from domain experts. Consequently, the scarcity of sufficient training data poses an obstacle to the progress of related models in this domain. In this paper, we propose ReactIE, which combines two weakly supervised approaches for pre-training. Our method utilizes frequent patterns within the text as linguistic cues to identify specific characteristics of chemical reactions. Additionally, we adopt synthetic data from patent records as distant supervision to incorporate domain knowledge into the model. Experiments demonstrate that ReactIE achieves substantial improvements and outperforms all existing baselines.Comment: Findings of ACL 2023, Short Pape

Exploiting Linked Data in Financial Engineering

Part 3: Finance and Service ScienceInternational audienceIn this paper, we report on a recent initiative that exploiting Linked Data for financial data integration. Financial data present high heterogeneity. Linked Data helps to reveal the true data semantics and “hidden” connection, upon which meaningful mappings can be constructed. The work reported in this paper has been well-accepted at several public events and conferences, including the 26th XBRL conference, involving the realisation of the XBRL (eXtensible Business Reporting Language) prototype called HIKAKU, which means “comparison” in Japanese. It demonstrates our approach to exploit the power of Linked Data in enhancing flexibility for data integration in the financial domain

Contribution of infrastructure to the township's sustainable development in Southwest China

Townships in Southwest China are usually located in mountainous regions, which are abundant in natural and cultural landscape resources. There are additional requirements for the township’s sustainable development in these areas. However, insufficient infrastructures, due to limited resources, constrain the sustainable development of these townships. Sustainable contribution of infrastructure (SCOI) in this study is defined as the performance of infrastructure as a contribution to the coordinated development among economic, social, and environmental dimensions of township’s sustainable development. It is necessary to assess these infrastructures according to SCOI and provide choices for investment to maximize resource utilization. Therefore, an assessing model of SCOI with 26 general indicators was developed, which covers five most urgently needed infrastructures of these townships in Southwest China, including road transport, sewage treatment, waste disposal, water supply, and gas. In this model, quantitative and qualitative methods are combined to acquire different SCOI of each infrastructure. The result of the SCOI would be an important reference for infrastructure investment. A case study of Jiansheng Town, that is located in the Dadukou district of Chongqing, demonstrates the applicability of the model. It shows the assessing model of SCOI is efficient to identify the most valuable infrastructure that is appropriate for investment with the goal of township’s sustainable development. This study can provide insights for infrastructure investment and management in townships or areas

Mapping the knowledge domains of emerging advanced technologies in the management of prefabricated construction

Emerging advanced technologies (EAT) have been regarded as significant technological innovations which can greatly improve the transforming construction industry. Given that research on EAT related to the management of prefabricated construction (MPC) has not yet been conducted, various researchers require a state-of-the-art summary of EAT research and implementation in the MPC field. The purpose of this paper is to provide a systematic literature review by analysing the selected 526 related publications in peer-reviewed leading journals during 2009–2020. Through a thorough review of selected papers from the state-of-the-art academic journals in the construction industry, EAT is recognised as the key area affecting the development of the MPC discipline. This study has value in offering original insights to summarise the advanced status quo of this field, helping subsequent researchers gain an in-depth understanding of the underlying structure of this field and allowing them to continue future research directions

Light-responsive expression atlas reveals the effects of light quality and intensity in Kalanchoë fedtschenkoi, a plant with crassulacean acid metabolism.

BackgroundCrassulacean acid metabolism (CAM), a specialized mode of photosynthesis, enables plant adaptation to water-limited environments and improves photosynthetic efficiency via an inorganic carbon-concentrating mechanism. Kalanchoë fedtschenkoi is an obligate CAM model featuring a relatively small genome and easy stable transformation. However, the molecular responses to light quality and intensity in CAM plants remain understudied.ResultsHere we present a genome-wide expression atlas of K. fedtschenkoi plants grown under 12 h/12 h photoperiod with different light quality (blue, red, far-red, white light) and intensity (0, 150, 440, and 1,000 μmol m-2 s-1) based on RNA sequencing performed for mature leaf samples collected at dawn (2 h before the light period) and dusk (2 h before the dark period). An eFP web browser was created for easy access of the gene expression data. Based on the expression atlas, we constructed a light-responsive co-expression network to reveal the potential regulatory relationships in K. fedtschenkoi. Measurements of leaf titratable acidity, soluble sugar, and starch turnover provided metabolic indicators of the magnitude of CAM under the different light treatments and were used to provide biological context for the expression dataset. Furthermore, CAM-related subnetworks were highlighted to showcase genes relevant to CAM pathway, circadian clock, and stomatal movement. In comparison with white light, monochrome blue/red/far-red light treatments repressed the expression of several CAM-related genes at dusk, along with a major reduction in acid accumulation. Increasing light intensity from an intermediate level (440 μmol m-2 s-1) of white light to a high light treatment (1,000 μmol m-2 s-1) increased expression of several genes involved in dark CO2 fixation and malate transport at dawn, along with an increase in organic acid accumulation.ConclusionsThis study provides a useful genomics resource for investigating the molecular mechanism underlying the light regulation of physiology and metabolism in CAM plants. Our results support the hypothesis that both light intensity and light quality can modulate the CAM pathway through regulation of CAM-related genes in K. fedtschenkoi

Understanding health and social challenges for aging and long-term care in China

The second King’s College London Symposium on Ageing and Long-term Care in China was convened from 4 to 5th July 2019 at King’s College London in London. The aim of the Symposium was to have a better understanding of health and social challenges for aging and long-term care in China. This symposium draws research insights from a wide range of disciplines, including economics, public policy, demography, gerontology, public health and sociology. A total of 20 participants from eight countries, seek to identify the key issues and research priorities in the area of aging and long-term care in China. The results published here are a synthesis of the top four research areas that represent the perspectives from some of the leading researchers in the field. © The Author(s) 2020

ADEPT:A dataset for evaluating prosody transfer

Text-to-speech is now able to achieve near-human naturalness and research focus has shifted to increasing expressivity. One popular method is to transfer the prosody from a reference speech sample. There have been considerable advances in using prosody transfer to generate more expressive speech, but the field lacks a clear definition of what successful prosody transfer means and a method for measuring it. We introduce a dataset of prosodically-varied reference natural speech samples for evaluating prosody transfer. The samples include global variations reflecting emotion and interpersonal attitude, and local variations reflecting topical emphasis, propositional attitude, syntactic phrasing and marked tonicity. The corpus only includes prosodic variations that listeners are able to distinguish with reasonable accuracy, and we report these figures as a benchmark against which text-to-speech prosody transfer can be compared. We conclude the paper with a demonstration of our proposed evaluation methodology, using the corpus to evaluate two text-to-speech models that perform prosody transfer.Comment: 5 pages, 1 figure, accepted to Interspeech 202

Ctrl-P:Temporal control of prosodic variation for speech synthesis

Text does not fully specify the spoken form, so text-to-speech models must be able to learn from speech data that vary in ways not explained by the corresponding text. One way to reduce the amount of unexplained variation in training data is to provide acoustic information as an additional learning signal. When generating speech, modifying this acoustic information enables multiple distinct renditions of a text to be produced. Since much of the unexplained variation is in the prosody, we propose a model that generates speech explicitly conditioned on the three primary acoustic correlates of prosody: $F_{0}$, energy and duration. The model is flexible about how the values of these features are specified: they can be externally provided, or predicted from text, or predicted then subsequently modified. Compared to a model that employs a variational auto-encoder to learn unsupervised latent features, our model provides more interpretable, temporally-precise, and disentangled control. When automatically predicting the acoustic features from text, it generates speech that is more natural than that from a Tacotron 2 model with reference encoder. Subsequent human-in-the-loop modification of the predicted acoustic features can significantly further increase naturalness.Comment: To be published in Interspeech 2021. 5 pages, 4 figure

An annotated checklist of vascular plants of Cherangani hills, Western Kenya

Cherangani hills, located in Western Kenya, comprises of 12 forest blocks, maintaining great plant diversity. However, little attention to plant diversity studies has been paid to it in the past years. Here, we present a checklist of the vascular plants of this region obtained through intensive field investigations and matching of herbarium specimens. In total, 1296 species, including 17 endemic species are documented, belonging to 130 families and 608 genera. This flora represents 18.50%, 43.83% and 54.17% of the Kenyan species, genera and families, respectively. The habit, habitat and voucher specimens, as well as brief notes on the distribution of each taxon recorded are presented in this checklist. It is the first exhaustive inventory of the terrestrial vascular plants in Cherangani hills which is a significant regional centre for plant diversity