Patient innovation (PI) activities in China: a combination of semi-quantitative and multi-case study approach

User innovation has been extensively and increasingly involved in the health sector in recent years. As a typical performance, patients and caregivers develop innovative solutions beyond professional medical treatment, aiming to better respond to the diseases. In addition, some of those innovations are shared with other patients in need, through non-commercial and commercial approaches. In practice, PI (www.patient-innovation.com) platform was established in 2014 in Portugal, on which 850 innovations from patients, caregivers and collaborators are shared, fulfilling the mission of adding value to other people’s lives. With the huge population base, there has been great diversity and significant regional differences in living, health and medical conditions among Chinese nations. Taken also the limited Reimbursement ratio of medical insurance, as well as the exposure to increasing innovation activities in recent years in China into account, those possibly act as incentives for patients and caregivers to develop innovated, alternative solutions besides medical treatments. In this research project, we will focus exclusively on the patient innovation (PI) activities in China, thanks to its great potential. We aim to understand the following questions: 1. Do PI activities actively happen in China? 2. What are the findings and typical examples of PI activities in China? 3. What are the characteristics of PI activities and the influencing factors of PI in China? What are the differences of PI China comparing with those in developed countries? Given the complexity of the research and the limitations of the information sources, in our research work, both a multi-case study (online search for publicly available PI activities) and a quantitative approach (survey among patients with chronic disease and caregivers) are applied. 55 online-available PI cases and 509 survey samples have been collected from China, which we’ve then screened and identified PI activities for further evaluation and statistical analysis. Our results have indicated a relatively activeness of PI activities in China with many practical examples. 1/3 patients or caregivers have reported innovation initiatives, and according to medical professionals, 13,5% have got a solution considered as reasonable, and 13,3% holds a meaningful idea, with many constraints possibly hinder implementation. Those PI activities has significantly improved the health and life quality, and some are shared with other people in need. Certain factors such as educational level and geographical region are likely to influence PI activities in China. In addition, PI activities in China shares some characteristics and influencing factors of those in Portugal, despite relatively simple and lower in technical contents

Pyrrole acetic acid derivatives in Lewis base catalyzed enantioselective formal [4+2] cycloadditions

This thesis describes the use of C(1) ammonium enolate chemistry with Lewis base isothiourea catalysis in Michael addition-lactonization/lactamization between 2-pyrrolyl acetic acid derivatives and various Michael acceptors. Chapter 2 proved the principle that amino esters protected as benzophenone Schiff base could be α-functionalized using Lewis base catalysis. Chapter 3 described the use of 2-pyrrolyl acetic acid in enantioselective Michael addition-lactonization with CCl3 enone. After in situ ring-opening, a range of 30 diesters and diamides in up to 98% yield, >95:5 dr and >99:1 er. Further demonstration of the synthetic utility of these ring-opening derivatives was achieved with an intramolecular Friedel-Crafts acylation utilizing the electron-rich nature of pyrrole to afforded dihydroindolizinone derivatives in up to 90% yield with no erosion in stereoselectivity. Chapter 4 described the use of either α,β-unsaturated trifluoromethyl ketones or α-keto-β,γ-unsaturated esters with 2-pyrrolyl acetic acid to synthesize tetrahydroindolizine derivatives in one-pot, with up to 98% yield, >95:5 dr and >99:1 er. Chapter 5 described the synthesis of dihydropyridinones from chalcone-derived N-Ts ketimine and unsaturated cyclic sulfonamide derived from saccharin in up to 97% yield, >95:5 dr and >99:1 er. Chapter 6 described the synthesis of tetrasubstituted pyridines using a variety of unsaturated ketimines bearing esters with DHPB catalyst in up to 66% yield. Further derivatization was demonstrated via transforming 2-pivaloyloxy group into 2-OTs group in a two-step process, enabling the Pd-catalyzed cross coupling and reduction

Eco-Translatology Perspective on the English Translation of Subtitles in the Documentary Eight Hundred Years of Chu State

Based on the concept of translational eco-environment, oriental ecological wisdom, and the Darwinian principle of natural selection, the concepts of eco-translatology and relevant theoretical ideas were proposed and explained by Professor Hu Gengshen from 2001 on. This interdisciplinary theory of translation studies and ecology considers translation as a translator's adaptation and selection activities, and its translation methods include the linguistic, cultural, and communication aspects. Eight Hundred Years of Chu State is a large-scale documentary about Chu culture. It systematically tells about the great history of the 800 years of Chu State, interpreting the brilliant and splendid civilization of Chu with its magnificent cultural relics, and revealing the laws worth pondering behind its ups and downs. Taking as examples the Chinese-English subtitle translations of the documentary Eight Hundred Years of Chu State, this paper aims to take the interdisciplinary theoretical perspective of eco-translatology to explore its implications for documentary translation from the linguistic, cultural, and communicative dimensions. Aiming also to improve the English translation of Chinese-made documentaries to a higher level, this paper hopes to promote the spread of Chinese traditional culture, especially Jingchu culture, and to enhance the world's understanding of China and its splendid culture

Research on Translation of Petroleum Technical English from the Perspective of Eco-Translatology

As a special category of English for science and technology, Petroleum Technical English (PTE) has rising importance with the development of petroleum industry. Combining general English with petroleum terminology and knowledge, its language is characterized by conciseness, accuracy, objectivity, logic and preciseness. From the perspective of Eco-translatology, and in light of the stylistic features of PTE, this article intends to explore the application of Eco-translatology theory on the translation of PTE from three dimensions: linguistic, cultural and communicative

PMU measurements based short-term voltage stability assessment of power systems via deep transfer learning

Deep learning has emerged as an effective solution for addressing the challenges of short-term voltage stability assessment (STVSA) in power systems. However, existing deep learning-based STVSA approaches face limitations in adapting to topological changes, sample labeling, and handling small datasets. To overcome these challenges, this paper proposes a novel phasor measurement unit (PMU) measurements-based STVSA method by using deep transfer learning. The method leverages the real-time dynamic information captured by PMUs to create an initial dataset. It employs temporal ensembling for sample labeling and utilizes least squares generative adversarial networks (LSGAN) for data augmentation, enabling effective deep learning on small-scale datasets. Additionally, the method enhances adaptability to topological changes by exploring connections between different faults. Experimental results on the IEEE 39-bus test system demonstrate that the proposed method improves model evaluation accuracy by approximately 20% through transfer learning, exhibiting strong adaptability to topological changes. Leveraging the self-attention mechanism of the Transformer model, this approach offers significant advantages over shallow learning methods and other deep learning-based approaches.Comment: Accepted by IEEE Transactions on Instrumentation & Measuremen

Surface structure and multigap superconductivity of V3Si (111) revealed by scanning tunneling microscopy

V3Si, a classical silicide superconductor with relatively high TC (~16 K), is promising for constructing silicon-based superconducting devices and hetero-structures. However, real space characterization on its surfaces and superconducting properties are still limited. Here we report the first low-temperature scanning tunnelling microscopy (STM) study on cleaned V3Si (111) single crystal surface. We observed a r3 by r3 superstructure which displays mirror symmetry between adjacent terraces, indicating the surface is V-terminated and reconstructed. The tunneling spectrum shows full superconducting gap with double pairs of coherence peaks, but has a relatively small gap size with comparing to bulk TC. Impurity induced in-gap state is absent on surface defects but present on introduced magnetic adatoms. Upon applying magnetic field, a hexagonal vortex lattice is visualized. Interestingly, the vortex size is found to be field dependent, and the coherence length measured from single vortex at low field is significantly larger than estimated value from bulk H_c2. These results reflect V3Si is a multi-band, s- wave superconductor

Targeted Poverty Alleviation and Households’ Livelihood Strategy in a Relation-Based Society: Evidence from Northeast China

Abstract: Although China is experiencing a transition from a relation-based society to a rule-based society, relationships among acquaintances still play an important role in resource allocation, such as the allocation of policy resources. This is particularly true in rural China, where targeted poverty alleviation is prevalent and a relation-based social structure still dominates. However, it is still unknown how relationships affect the livelihood strategy of households in rural China and how poverty alleviation policies plays a role between them. Therefore, this paper embeds poverty alleviation into the relation-based society and explores how households respond to the policy in this specific context. Using grounded theory research method and the sustainable livelihoods approach (SLA) framework, this paper contains in-depth interviews and field observations from three povertystricken villages in Northeast China. The results show that relationships have a significant impact on the households’ livelihood strategy. In other words, the households’ livelihood strategy is embedded in the relation-based society. The types of relationships induce households to choose maintained or developmental type livelihood strategies, while relationships influence how the poverty alleviation policies affect the livelihood strategy. This study is not only an extension of the SLA in the research context, but also provides a significant perspective for enriching the long-term mechanism of targeted poverty alleviation by building a theoretical model of the relationships between a relation-based society, targeted poverty alleviation and the livelihood strategies of households.publishedVersio

End-to-End Lyrics Recognition with Self-supervised Learning

Lyrics recognition is an important task in music processing. Despite traditional algorithms such as the hybrid HMM- TDNN model achieving good performance, studies on applying end-to-end models and self-supervised learning (SSL) are limited. In this paper, we first establish an end-to-end baseline for lyrics recognition and then explore the performance of SSL models on lyrics recognition task. We evaluate a variety of upstream SSL models with different training methods (masked reconstruction, masked prediction, autoregressive reconstruction, and contrastive learning). Our end-to-end self-supervised models, evaluated on the DAMP music dataset, outperform the previous state-of-the-art (SOTA) system by 5.23% for the dev set and 2.4% for the test set even without a language model trained by a large corpus. Moreover, we investigate the effect of background music on the performance of self-supervised learning models and conclude that the SSL models cannot extract features efficiently in the presence of background music. Finally, we study the out-of-domain generalization ability of the SSL features considering that those models were not trained on music datasets.Comment: 4 pages, 2 figures, 3 table