Natural Language Processing Using Neighbour Entropy-based Segmentation

In natural language processing (NLP) of Chinese hazard text collected in the process of hazard identification, Chinese word segmentation (CWS) is the first step to extracting meaningful information from such semi-structured Chinese texts. This paper proposes a new neighbor entropy-based segmentation (NES) model for CWS. The model considers the segmentation benefits of neighbor entropies, adopting the concept of "neighbor" in optimization research. It is defined by the benefit ratio of text segmentation, including benefits and losses of combining the segmentation unit with more information than other popular statistical models. In the experiments performed, together with the maximum-based segmentation algorithm, the NES model achieves a 99.3% precision, 98.7% recall, and 99.0% f-measure for text segmentation; these performances are higher than those of existing tools based on other seven popular statistical models. Results show that the NES model is a valid CWS, especially for text segmentation requirements necessitating longer-sized characters. The text corpus used comes from the Beijing Municipal Administration of Work Safety, which was recorded in the fourth quarter of 2018

Viability Discrimination of a Class of Control Systems on a Nonsmooth Region

The viability problem is an important field of study in control theory; the corresponding research has profound significance in both theory and practice. In this paper, we consider the viability for both an affine nonlinear hybrid system and a hybrid differential inclusion on a region with subdifferentiable boundary. Based on the nonsmooth analysis theory, we obtain a method to verify the viability condition at a point, when the boundary function of the region is subdifferentiable and its subdifferential is convex hull of many finite points

Topic evolution and sentiment comparison of user reviews on an online medical platform in response to COVID-19: taking review data of Haodf.com as an example

IntroductionThroughout the COVID-19 pandemic, many patients have sought medical advice on online medical platforms. Review data have become an essential reference point for supporting users in selecting doctors. As the research object, this study considered Haodf.com, a well-known e-consultation website in China.MethodsThis study examines the topics and sentimental change rules of user review texts from a temporal perspective. We also compared the topics and sentimental change characteristics of user review texts before and after the COVID-19 pandemic. First, 323,519 review data points about 2,122 doctors on Haodf.com were crawled using Python from 2017 to 2022. Subsequently, we employed the latent Dirichlet allocation method to cluster topics and the ROST content mining software to analyze user sentiments. Second, according to the results of the perplexity calculation, we divided text data into five topics: diagnosis and treatment attitude, medical skills and ethics, treatment effect, treatment scheme, and treatment process. Finally, we identified the most important topics and their trends over time.ResultsUsers primarily focused on diagnosis and treatment attitude, with medical skills and ethics being the second-most important topic among users. As time progressed, the attention paid by users to diagnosis and treatment attitude increased—especially during the COVID-19 outbreak in 2020, when attention to diagnosis and treatment attitude increased significantly. User attention to the topic of medical skills and ethics began to decline during the COVID-19 outbreak, while attention to treatment effect and scheme generally showed a downward trend from 2017 to 2022. User attention to the treatment process exhibited a declining tendency before the COVID-19 outbreak, but increased after. Regarding sentiment analysis, most users exhibited a high degree of satisfaction for online medical services. However, positive user sentiments showed a downward trend over time, especially after the COVID-19 outbreak.DiscussionThis study has reference value for assisting user choice regarding medical treatment, decision-making by doctors, and online medical platform design

Reconfigurable Inverted Index

Existing approximate nearest neighbor search systems suffer from two fundamental problems that are of practical importance but have not received sufficient attention from the research community. First, although existing systems perform well for the whole database, it is difficult to run a search over a subset of the database. Second, there has been no discussion concerning the performance decrement after many items have been newly added to a system. We develop a reconfigurable inverted index (Rii) to resolve these two issues. Based on the standard IVFADC system, we design a data layout such that items are stored linearly. This enables us to efficiently run a subset search by switching the search method to a linear PQ scan if the size of a subset is small. Owing to the linear layout, the data structure can be dynamically adjusted after new items are added, maintaining the fast speed of the system. Extensive comparisons show that Rii achieves a comparable performance with state-of-the art systems such as Faiss.Comment: ACMMM 2018 (oral). Code: https://github.com/matsui528/ri

Genetic characterization and linkage disequilibrium mapping of resistance to gray leaf spot in maize (Zea mays L.)

AbstractGray leaf spot (GLS), caused by Cercospora zeae-maydis, is an important foliar disease of maize (Zea mays L.) worldwide, resistance to which is controlled by multiple quantitative trait loci (QTL). To gain insights into the genetic architecture underlying the resistance to this disease, an association mapping population consisting of 161 inbred lines was evaluated for resistance to GLS in a plant pathology nursery at Shenyang in 2010 and 2011. Subsequently, a genome-wide association study, using 41,101 single-nucleotide polymorphisms (SNPs), identified 51 SNPs significantly (P<0.001) associated with GLS resistance, which could be converted into 31 QTL. In addition, three candidate genes related to plant defense were identified, including nucleotide-binding-site/leucine-rich repeat, receptor-like kinase genes similar to those involved in basal defense. Two genic SNPs, PZE-103142893 and PZE-109119001, associated with GLS resistance in chromosome bins 3.07 and 9.07, can be used for marker-assisted selection (MAS) of GLS resistance. These results provide an important resource for developing molecular markers closely linked with the target trait, enhancing breeding efficiency

Inhibition of differentiation of monocyte-derived macrophages toward an M2-Like phenotype May Be a neglected mechanism of β-AR receptor blocker therapy for atherosclerosis

The clinical efficacy of adrenergic β-receptor (β-AR) blockers in significantly stabilizing atherosclerotic plaques has been extensively supported by evidence-based medical research; however, the underlying mechanism remains unclear. Recent findings have highlighted the impact of lipid-induced aberrant polarization of macrophages during normal inflammatory-repair and regenerative processes on atherosclerosis formation and progression. In this review, we explore the relationship between macrophage polarization and atherosclerosis, as well as the influence of β-AR blockers on macrophage polarization. Based on the robust evidence supporting the use of β-AR blockers for treating atherosclerosis, we propose that their main mechanism involves inhibiting monocyte-derived macrophage differentiation towards an M2-like phenotype

A High-Performance Mid-infrared Optical Switch Enabled by Bulk Dirac Fermions in Cd3As2

Pulsed lasers operating in the 2-5 {\mu}m band are important for a wide range of applications in sensing, spectroscopy, imaging and communications. Despite recent advances with mid-infrared gain media, the lack of a capable pulse generation mechanism, i.e. a passive optical switch, remains a significant technological challenge. Here we show that mid-infrared optical response of Dirac states in crystalline Cd3As2, a three-dimensional topological Dirac semimetal (TDS), constitutes an ideal ultrafast optical switching mechanism for the 2-5 {\mu}m range. Significantly, fundamental aspects of the photocarrier processes, such as relaxation time scales, are found to be flexibly controlled through element doping, a feature crucial for the development of convenient mid-infrared ultrafast sources. Although various exotic physical phenomena have been uncovered in three-dimensional TDS systems, our findings show for the first time that this emerging class of quantum materials can be harnessed to fill a long known gap in the field of photonics.Comment: 17 pages, 3 figure