Improving Aspen Kraft Pulp by A Novel, Low-Technology Fungal Pretreatment

This study investigated the biopulping agent Phanerochaete chrysosporium with a new process that required neither wood sterilization nor pure culture incubation conditions. Aspen (Populus tremuloides Michaux) chip bales with three treatments were studied. Each bale was kraft cooked after 8.5 weeks of pretreatment. The effects of fungal inoculation and foil-wrapping on pulp and paper strength properties were evaluated. Fungal pretreatment caused significantly faster response to beating as lower freeness was noted. Foil-wrapping retarded the loss of moisture within the bale, and as a result, prolonged fungal activities, resulting in substantial increases in burst strength. Tear was slightly increased, but there was no increase in tensile strength. In some bales, brightness of unbleached pulp was reduced. This study has shown that substantial improvements in certain paper properties and potential beating energy savings could be achieved through this compression/baling technique. Optimization of this system has the potential to provide a practical method of chip pretreatment for the pulp and paper industry

Order-Preserving Abstractive Summarization for Spoken Content Based on Connectionist Temporal Classification

Connectionist temporal classification (CTC) is a powerful approach for sequence-to-sequence learning, and has been popularly used in speech recognition. The central ideas of CTC include adding a label "blank" during training. With this mechanism, CTC eliminates the need of segment alignment, and hence has been applied to various sequence-to-sequence learning problems. In this work, we applied CTC to abstractive summarization for spoken content. The "blank" in this case implies the corresponding input data are less important or noisy; thus it can be ignored. This approach was shown to outperform the existing methods in term of ROUGE scores over Chinese Gigaword and MATBN corpora. This approach also has the nice property that the ordering of words or characters in the input documents can be better preserved in the generated summaries.Comment: Accepted by Interspeech 201

Effective government affairs in an era of marketization: Strategic issues management, business lobbying, and relationship management by multinational corporations in China

Little public relations research on government affairs has been conducted. Even less research of this kind has yet been conducted in a non-western context. The purposes of this study were to explore how public relations professionals in multinational corporations (MNCs) in China practice government affairs activities at different levels of Chinese government and to develop a normative theory of strategic government affairs. Government affairs in this dissertation refers to the organizational function that encompasses issues management, policy formation, and relationship management. I applied the perspectives of public relations and political economy to examine the MNCs' management of government affairs. I conducted 27 long interviews with executives or managers responsible for government affairs from the China offices of 25 MNCs. The MNCs cover several industries and three business entry modes. I also conducted a two-phase document review and informal interviews with Chinese journalists and public relations scholars and practitioners. My data suggested that with China's socialist market economy and authoritarian political system, MNCs must interact with the government to strategically manage opportunities and threats in their environments. I found that government affairs performs six functions. Government affairs contributes to organizational effectiveness by participating in the MNCs' strategic management processes through four roles, managing issues, and cultivating the MNCs' relationships with key stakeholders through communication and corporate behaviors. My data showed common political strategies and consistent patterns of political involvement of the MNCs. MNCs selected their political strategies based on factors such as economic conditions and organizational characteristics. Only a few MNCs evaluated their government affairs practices based on goal achievement. Drawing on the results, I developed three models that construct my theory of strategic government affairs. These models apply general public relations theories to the context of government affairs. The model of strategic management of government affairs identifies government affairs' participation in an organization's strategic management and the strategic nature of government affairs programs. The situational theory for government affairs allows professionals to separate active publics from stakeholders. The model of effective government affairs provides a framework for the development of government affairs programs that reflect long-term strategic management

Effect of Compression of Green Wood Chips on Conidial Germination and Colonization of A Biopulping Fungus, Phanerochaete Chrysosporium

Compression and baling of green wood ships inoculated with a biopulping fungus Phanerochaete chrysosporium has produced pulps with increased strength properties and reduced energy inputs without the need for steaming of chips or specialized bioreactor conditions. Use of a contact-agar method to study spore germination has shown that compression of green wood enhances rates of sapwood colonization by two strains of this white-rot fungus. This response was verified by SEM observation and is thought to occur as a result of parenchyma death during chip compression. The colonization of this fungus on softwood chips was also improved as a result of compression

Yin-yang Balance Therapy on Regulating Cancer Stem Cells

AbstractsResearches have shown that cancer stem cells, regulated by the niche where they reside, are the roots of oncogenesis, relapse and metastasis. To date, very few treatments have targeted on cancer stem cells. The authors study that the regulated factors in the niche share the characteristics of yin-yang in the theory of traditional Chinese medicine, which has confirmed its therapeutic effects in the prevention and treatment of cancer. So the authors presume that the mechanisms of traditional Chinese medicine on the prevention and treatment of cancer may be related to the yin-yang balance of the niche of cancer stem cells

Correlation of Copper Interaction, Copper-Driven Aggregation, and Copper-Driven H2O2 Formation with Aβ40 Conformation

The neurotoxicity of Aβ is associated with the formation of free radical by interacting with redox active metals such as Cu2+. However, the relationship between ion-interaction, ion-driven free radical formation, and Aβ conformation remains to be further elucidated. In the present study, we investigated the correlation of Cu2+ interaction and Cu2+-driven free radical formation with Aβ40 conformation. The Cu2+-binding affinity for Aβ40 in random coiled form is 3-fold higher than that in stable helical form. Unexpectedly but interestingly, we demonstrate in the first time that the stable helical form of Aβ40 can induce the formation of H2O2 by interacting with Cu2+. On the other hand, the H2O2 generation is repressed at Aβ/Cu2+ molar ratio ≥1 when Aβ40 adopts random coiled structure. Taken together, our result demonstrates that Aβ40 adopted a helical structure that may play a key factor for the formation of free radical with Cu2+ ions

AdapterBias: Parameter-efficient Token-dependent Representation Shift for Adapters in NLP Tasks

Transformer-based pre-trained models with millions of parameters require large storage. Recent approaches tackle this shortcoming by training adapters, but these approaches still require a relatively large number of parameters. In this study, AdapterBias, a surprisingly simple yet effective adapter architecture, is proposed. AdapterBias adds a token-dependent shift to the hidden output of transformer layers to adapt to downstream tasks with only a vector and a linear layer. Extensive experiments are conducted to demonstrate the effectiveness of AdapterBias. The experiments show that our proposed method can dramatically reduce the trainable parameters compared to the previous works with a minimal decrease in task performances compared with fine-tuned pre-trained models. We further find that AdapterBias automatically learns to assign more significant representation shifts to the tokens related to the task in consideration.Comment: The first two authors contributed equally. This paper was published in Findings of NAACL 202