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"tung"
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Rival Partners
Taiwan has been depicted as an island facing the incessant threat of forcible unification with the People's Republic of China. Why, then, has Taiwan spent more than three decades pouring capital and talent into China?In award-winning Rival Partners, Wu Jieh-min follows the development of Taiwanese enterprises in China over twenty-five years and provides fresh insights. The geopolitical shift in Asia beginning in the 1970s and the global restructuring of value chains since the 1980s created strong incentives for Taiwanese entrepreneurs to rush into China despite high political risks and insecure property rights. Taiwanese investment, in conjunction with Hong Kong capital, laid the foundation for the world’s factory to flourish in the southern province of Guangdong, but official Chinese narratives play down Taiwan’s vital contribution. It is hard to imagine the Guangdong model without Taiwanese investment, and, without the Guangdong model, China’s rise could not have occurred. Going beyond the received wisdom of the “China miracle\" and “Taiwan factor,\" Wu delineates how Taiwanese businesspeople, with the cooperation of local officials, ushered global capitalism into China. By partnering with its political archrival, Taiwan has benefited enormously, while helping to cultivate an economic superpower that increasingly exerts its influence around the world.
eBook
The shape of a life : one mathematician's search for the universe's hidden geometry
\"Harvard geometer and Fields medalist Shing-Tung Yau has provided a mathematical foundation for string theory, offered new insights into black holes, and mathematically demonstrated the stability of our universe. In this autobiography, Yau reflects on his improbable journey to becoming one of the world's most distinguished mathematicians. Beginning with an impoverished childhood in China and Hong Kong, Yau takes readers through his doctoral studies at Berkeley during the height of the Vietnam War protests, his Fields Medal-winning proof of the Calabi conjecture, his return to China, and his pioneering work in geometric analysis. This new branch of geometry, which Yau built up with his friends and colleagues, has paved the way for solutions to several important and previously intransigent problems. With complicated ideas explained for a broad audience, this book offers readers not only insights into the life of an eminent mathematician, but also an accessible way to understand advanced and highly abstract concepts in mathematics and theoretical physics\"--Publisher's website.
Book
DCAMCP : A deep learning model based on capsule network and attention mechanism for molecular carcinogenicity prediction
The carcinogenicity of drugs can have a serious impact on human health, so carcinogenicity testing of new compounds is very necessary before being put on the market. Currently, many methods have been used to predict the carcinogenicity of compounds. However, most methods have limited predictive power and there is still much room for improvement. In this study, we construct a deep learning model based on capsule network and attention mechanism named DCAMCP to discriminate between carcinogenic and non‐carcinogenic compounds. We train the DCAMCP on a dataset containing 1564 different compounds through their molecular fingerprints and molecular graph features. The trained model is validated by fivefold cross‐validation and external validation. DCAMCP achieves an average accuracy (ACC) of 0.718 ± 0.009, sensitivity (SE) of 0.721 ± 0.006, specificity (SP) of 0.715 ± 0.014 and area under the receiver‐operating characteristic curve (AUC) of 0.793 ± 0.012. Meanwhile, comparable results can be achieved on an external validation dataset containing 100 compounds, with an ACC of 0.750, SE of 0.778, SP of 0.727 and AUC of 0.811, which demonstrate the reliability of DCAMCP. The results indicate that our model has made progress in cancer risk assessment and could be used as an efficient tool in drug design.
Journal Article
The complete chloroplast genomes and comparative study of the two tung trees of Vernicia (Euphorbiaceae)
Background
Vernicia montana
and
V
.
fordii
are economically important woody oil species in the Euphorbiaceae that have great industrial oil and ornamental greening properties, however, the wild resources of
Vernicia
trees have been reduced because of their habitat destruction. Considering the diverse economic and ecological importance of
Vernicia
species, it is important to collect more molecular data to determine the genetic differences between
V. montana
and
V. fordii
.
Results
We sequenced, assembled, and annotated the complete chloroplast (CP) genome of two tung trees based on the genome skimming approach. The whole CP genomes of
V. montana and V. fordii
were 163,518 bp and 161,495 bp in length, both including a pair of inverted repeats separated by a large single-copy and a small single-copy region. We detected a total number of 311 tandem repeats, 100 dispersed repeats, and 255 simple repeats from
V. montana
and
V. fordii
CP genomes. The mean value of nucleotide diversity between the two species was 0.0122, and the average Ka/Ks ratio across all coding genes was 0.3483. Comparative chloroplast genome analysis showed that the coding regions were more conserved than the non-coding regions. The phylogenetic relationships yielded by the complete genome sequences showed that
V. montana
was closely related to
V. fordii
and is considered as a sister group.
Conclusions
We sequenced, assembled, annotated, and analyzed the CP genome of two tung trees, which will be useful in investigating the conservation genetics and potential breeding applications of this oil shrub.
Journal Article
Enhancing Dental Material Performance: Tung Oil-Infused Polyurea Microcapsule Coatings for Self-Healing and Antimicrobial Applications
Within the realm of dental material innovation, this study pioneers the incorporation of tung oil into polyurea coatings, setting a new precedent for enhancing self-healing functionality and durability. Originating from an ancient practice, tung oil is distinguished by its outstanding water resistance and microbial barrier efficacy. By synergizing it with polyurea, we developed coatings that unite mechanical strength with biological compatibility. The study notably quantifies self-healing efficiency, highlighting the coatings’ exceptional capacity to mend physical damages and thwart microbial incursions. Findings confirm that tung oil markedly enhances the self-repair capabilities of polyurea, leading to improved wear resistance and the inhibition of microbial growth, particularly against Streptococcus mutans, a principal dental caries pathogen. These advancements not only signify a leap forward in dental material science but also suggest a potential redefinition of dental restorative practices aimed at prolonging the lifespan of restorations and optimizing patient outcomes. Although this study lays a substantial foundation for the utilization of natural oils in the development of medical-grade materials, it also identifies the critical need for comprehensive cytotoxicity assays. Such evaluations are essential to thoroughly assess the biocompatibility and the safety profile of these innovative materials for clinical application. Future research will concentrate on this aspect, ensuring that the safety and efficacy of the materials align with clinical expectations for dental restorations.
Journal Article
Extended Rauch–Tung–Striebel Smoother for the State of Charge Estimation of Lithium-Ion Batteries Based on an Enhanced Circuit Model
The state of charge (SOC) of a lithium battery system is critical since it indicates the remaining operating hours, full charge time, and peak power of the battery. This paper recommends an extended Rauch–Tung–Striebel smoother (ERTSS) for estimating SOC. It is implemented based on an improved equivalent circuit model with hysteresis voltage. The smoothing step of ERTSS will reduce the estimation error further. Additionally, the genetic algorithm (GA) is employed for searching the optimal ERTSS’s smoothing time interval. Various dynamic cell tests are conducted to verify the model’s accuracy and error estimation deviation. The test results demonstrate that ERTSS’s SOC estimation error is limited to 4% with an initial error between −25 ∘C and 45 ∘C and that the root mean square error (RMSE) of ERTSS’s SOC estimation is approximately 5% lower than that of extended Kalman filter (EKF). The ERTSS improves the SOC estimation accuracy at all operating temperatures of batteries.
Journal Article
Update on the role of antiseptics in the management of chronic wounds with critical colonisation and/or biofilm
Biofilms play a major role in delaying chronic wounds from healing. A wound infiltrated with biofilm, or “critically colonised” wound, may become clinically infected if the number of microbes exceeds a critical level. Chronic wound biofilms represent a significant treatment challenge by demonstrating recalcitrance towards antimicrobial agents. However, a “window of opportunity” may exist after wound debridement when biofilms are more susceptible to topical antiseptics. Here, we discuss the role of antiseptics in the management of chronic wounds and biofilm, focusing on povidone‐iodine (PVP‐I) in comparison with two commonly used antiseptics: polyhexanide (PHMB) and silver. This article is based on the literature reviewed during a focus group meeting on antiseptics in wound care and biofilm management, and on a PubMed search conducted in March 2020. Compared with PHMB and silver, PVP‐I has a broader spectrum of antimicrobial activity, potent antibiofilm efficacy, no acquired bacterial resistance or cross‐resistance, low cytotoxicity, good tolerability, and an ability to promote wound healing. PVP‐I represents a viable therapeutic option in wound care and biofilm management, with the potential to treat biofilm‐infiltrated, critically colonised wounds. We propose a practical algorithm to guide the management of chronic, non‐healing wounds due to critical colonisation or biofilm, using PVP‐I.
Journal Article