Hot Topic Discovery in Online Community using Topic Labels and Hot Features

With huge volumes of information on Internet, how to extract user-concerned hot topics quickly and effectively has become a fundamental task for information processing on Internet. Generally, hot topic detection includes two tasks, the first one is topic discovery and the other is its hotness evaluation. In this paper, we propose a hot topic detection method. For topic discovery, topics are identified by clustering based on extracted topic labels. For hotness evaluation, the proposed model has fully considered the internal and external dual features and combined them together. The experimental results over TianYa BBS demonstrate the efficiency of the proposed method: compared with topic discovery based on latent semantic indexing, the improved vector space model based on topic labels gets better results and the identified topics are more accurate. Moreover, the proposed hotness features could reflect the popularity of a topic, and hence have obtained better hot topic results finally

A Momentum Theory for Hot Topic Life-cycle: A Case Study of Hot Hashtag Emerging in Twitter

The existing work on mining of hot topics is mainly based on topic multiplicity andattention from users in unit time. With the advent of social networking, the weight has been put on the hot topics which can effectively describe the importance and hotness of a topic. However, the researches on the influence exerted by the accumulation of attention towards hot topics and the alternation between hot topics and outdated ones are still relatively weak. In this paper, a novel algorithm for calculating the hotness of topics is proposed based on momentum. The number of the participants, but also the long tail effect of the historical accumulation on the topic is taken into consideration. Through this algorithm, we can accurately build a model for the hot topics on their emerging growing period and effectively describe the whole life circle of the topic. Additionally, the change between hot topics and old ones can be distinguished efficiently. Our experiments show that the process of a topic growing into a hot topic can be detected explicitly. Potential hot topics can be explored and the overdue ones can be rejected respectively

An artificial intelligence driven multi-feature extraction scheme for big data detection

© 2019 IEEE. The Internet improves the speed of information dissemination, and the scale of unstructured text data is expanding and increasingly being used for mass communication. Although these large amounts of data meet the infinite demand, it is difficult to find public focus in a timely manner. Therefore, information extraction from big data has become an important research issue, and there are many published studies on big data processing at home and abroad. In this paper, we propose a multi-feature keyword extraction method, and based on this, an artificial intelligence driven big data MFE scheme is designed, then an application example of the general scheme is expanded and detailed. Taking news as the carrier, this scheme is applied to the algorithm design of hot event detection. As a result, a multi-feature fusion clustering algorithm is proposed based on user attention with two main stages. In the first stage, a multi-feature fusion model is developed to evaluate keywords, and this model combines the term frequency and part of speech features. We use it to extract keywords for representing news and events. In the second stage, we perform clustering and detect hot events in accordance with the procedure, and during the composition of news clusters, we analyze several variadic parameters in order to explore the optimal effectiveness. Then, experiments on the news corpus are conducted, and the results show that the approach presented herein performs well

Intelligent Sensors for Human Motion Analysis

The book, "Intelligent Sensors for Human Motion Analysis," contains 17 articles published in the Special Issue of the Sensors journal. These articles deal with many aspects related to the analysis of human movement. New techniques and methods for pose estimation, gait recognition, and fall detection have been proposed and verified. Some of them will trigger further research, and some may become the backbone of commercial systems

New innovations in pavement materials and engineering: A review on pavement engineering research 2021

Sustainable and resilient pavement infrastructure is critical for current economic and environmental challenges. In the past 10 years, the pavement infrastructure strongly supports the rapid development of the global social economy. New theories, new methods, new technologies and new materials related to pavement engineering are emerging. Deterioration of pavement infrastructure is a typical multi-physics problem. Because of actual coupled behaviors of traffic and environmental conditions, predictions of pavement service life become more and more complicated and require a deep knowledge of pavement material analysis. In order to summarize the current and determine the future research of pavement engineering, Journal of Traffic and Transportation Engineering (English Edition) has launched a review paper on the topic of “New innovations in pavement materials and engineering: A review on pavement engineering research 2021”. Based on the joint-effort of 43 scholars from 24 well-known universities in highway engineering, this review paper systematically analyzes the research status and future development direction of 5 major fields of pavement engineering in the world. The content includes asphalt binder performance and modeling, mixture performance and modeling of pavement materials, multi-scale mechanics, green and sustainable pavement, and intelligent pavement. Overall, this review paper is able to provide references and insights for researchers and engineers in the field of pavement engineering

Understanding cone photoreceptor dystrophies : from animal models to engineered patient-derived retinal tissues

La vision est considérée comme un des sens les plus importants, prenant en charge environ 80% des perceptions que nous recevons dans notre vie quotidienne. Les photorécepteurs de type cônes sont responsables de la vision centrale de haute résolution et en couleurs, et leur dégénérescence est souvent la cause de la perte de vision dans les maladies dégénératives rétiniennes (RDs). Les RDs sont un groupe hétérogène de maladies affectant des millions de personnes dans le monde, qui pour le moment sont pour la plupart sans aucune option thérapeutique. Les modèles animaux sont extrêmement utiles pour étudier le développement ou la dégénérescence de la rétine, ainsi que pour comprendre les mécanismes moléculaires des maladies génétiques héréditaires affectant les photorécepteurs. La modélisation des maladies dégénératives et du développement peut être particulièrement difficile, spécialement dans le cas de maladies humaines rares et complexes pour lesquelles aucun modèle animal exhaustif n'est disponible. De nos jours, la génération et le maintien de modèles de maladies humaines permettant une analyse approfondie du mécanisme moléculaire représente un grand défis . La technologie des cellules souches possède un grand potentiel dans la modélisation des maladies et représente un outil puissant pour générer des modèles évolutifs, sans l’utilisation d’animaux qui peuvent illustrer plus précisément les phénotypes cliniques de maladies humaines complexes. Nous avons développé un protocole pour différencier les cellules souches pluripotentes (PSCs) en feuillets rétiniens (RSs), qui sont des tissus polarisés et multicouches contenant des photorécepteurs cône et exprimant les marqueurs spécifiques du segment externe (OS), du cilium connecteur (CC) et du noyau. En utilisant à la fois des modèles de souris et des modèles humanisés à base de cellules souches, nous avons étudié le rôle de BMI1 dans les photorécepteurs matures. La protéine du groupe Polycomb Bmi1 est connue pour ses fonctions neuroprotectrices en contrôlant la sénescence et l'apoptose, et est exprimée à la fois dans le progéniteur rétinien et les neurones, mais on en sait peu sur son rôle spécifique dans la rétine adulte. Elle a été récemment associée à des troubles neurodégénératifs d'apparition tardive, et elle pourrait avoir un rôle dans la pathologie des RDs d'apparition tardive, comme la dégénérescence maculaire liée à l'âge (DMLA). Nous avons montré que les photorécepteurs cône et les neurones bipolaires sont générés normalement mais subissent ensuite une dégénérescence rapide chez les souris Bmi1-/- par nécroptose associée à Rip3. La dégénérescence était associée à des anomalies de compactage de la chromatine, à l'activation des répétitions en tandem et au stress oxydatif. De plus, nous montrons que BMI1 est préférentiellement exprimé dans les cônes au niveau des foyers hétérochromatiques dans la rétine humaine. Son inactivation dans les cellules souches embryonnaires humaines (hESCs) a altéré la différenciation terminale du cône et a entraîné des anomalies de compactage de la chromatine, l'activation des répétitions en tandem et l'induction de P53. Ces résultats fournissent un mécanisme expliquant comment une carence en Bmi1 conduit à la dégénérescence des cônes et révèlent des fonctions biologiques conservées et des différences pour Bmi1 dans la biologie des photorécepteurs entre la souris et l'homme. En utilisant un modèle humain basé sur les cellules souches pluripotentes induites (iPSCs), nous avons ensuite étudié le processus dégénératif chez les patients atteints de ciliopathies, un groupe de maladies génétiques hétérogènes affectant les protéines impliquées dans la structure et la fonction du cil primaire, qui sont fréquemment accompagnée d'une dégénérescence rétinienne. Nous générons des feuillets rétiniens dérivés d'iPSCs à partir de patients atteints de deux ciliopathies, les syndromes de Meckel-Gruber (MKS) et de Bardet-Biedl (BBS). Les photorécepteurs ciliopathiques présentaient des altérations communes significatives dans l'expression de centaines de gènes de développement. De plus, ils ont montré plusieurs anomalies dans la formation et le maintien du cilium interne, le positionnement du centriole mère, l'activation d'une réponse au stress aux protéines mal repliées, instabilités génomiques et l'accumulation de dommages à l'ADN. Cette étude révèle comment la combinaison des technologies de reprogrammation cellulaire et d'organogenèse avec le séquençage de nouvelle génération permet d'élucider les mécanismes moléculaires et cellulaires impliqués dans les troubles dégénératifs et développementaux de la rétine humaine. La même approche, combinant la différenciation en RSs avec des techniques de séquençage du génome à large spectre, pourrait être appliquée pour modéliser de nombreuses maladies génétiques, développementales et dégénératives affectant les photorécepteurs. Il peut également aider à élucider les mécanismes moléculaires sous-jacents à ces maladies, au criblage de médicaments de composés ayant des effets thérapeutiques potentiels et à prédire les effets secondaires des médicaments.Vision is considered the most important sense, taking on about 80% of the perceptions we receive in our everyday life. Cone-photoreceptors are responsible for high-resolution central vision and color discrimination, and their degeneration is frequently the cause of vision loss in retinal degenerative diseases (RDs). RDs are a heterogeneous group of diseases affecting millions of people worldwide, which at the moment are mostly without any therapeutic option. Animal models are extremely useful in studying the retina's development or degeneration and understanding the molecular mechanisms in inherited genetic disease affecting photoreceptors. Modeling human developmental and degenerative diseases can be particularly challenging, especially in the case of rare and complex diseases where no exhaustive animal models are available. Generation of sustainable human disease models that allow in-depth analysis of the molecular mechanism is one of the big challenges nowadays. Stem cell technology holds great potential in disease modeling and represents a new powerful tool for generating scalable and animal-free models that can more accurately illustrate clinical phenotypes of complex human diseases. We developed a protocol to differentiate pluripotent stem cells (PSCs) into retinal sheets (RSs), which are polarized, multi-layered tissues containing cone photoreceptors and expressing outer segment (OS), connecting cilium (CC), and nuclear specific markers. Using both mouse and stem cells-based humanized models, we first investigate the role of BMI1 in mature photoreceptors. The Polycomb group protein Bmi1 is known for its neuroprotective functions by controlling senescence and apoptosis and is expressed in both retinal progenitor and neurons, but little is known about its specific role in the adult retina. It has been recently linked to late-onset neurodegenerative disorders, and it could have a role in the pathology of late-onset RDs, such as Age-related Macular Degeneration (AMD). We showed that cone photoreceptors and bipolar neurons are generated normally but then undergo rapid degeneration in Bmi1-/- mice through Rip3-associated necroptosis. Degeneration was associated with chromatin compaction anomalies, activation of tandem-repeats, and oxidative stress. Furthermore, we show that BMI1 is preferentially expressed in cones at heterochromatic foci in the human retina. Its inactivation in human embryonic stem cells (hESCs) impaired cone terminal differentiation and resulted in chromatin compaction anomalies, activation of tandem-repeats, and P53 induction. These findings provide a mechanism explaining how Bmi1 deficiency leads to cone degeneration and reveal conserved biological functions and differences for Bmi1 in photoreceptor biology between mouse and man. Using an induced Pluripotent Stem Cells (iPSCs) based human model, we then investigate the degenerative process in patients with ciliopathies, a group of heterogeneous genetic diseases affecting proteins involved in primary cilium structure and function frequently accompanied by retinal degeneration. We generate iPSC-derived retinal sheets from patients affected by two ciliopathies, Meckel-Gruber (MKS) and Bardet-Biedl syndromes (BBS). Ciliopathic photoreceptors displayed significant common alterations in the expression of hundreds of developmental genes. Moreover, they showed several anomalies in the formation and maintenance of cilia, the mother centriole's positioning, the activation of a stress response to misfolded proteins, genomic instabilities, and DNA damage accumulation. This study reveals how combining cell reprogramming and organogenesis technologies with next-generation sequencing enables the elucidation of molecular and cellular mechanisms involved in human retinal degenerative and developmental disorders. The same approach, combining photoreceptor sheet differentiation and wide-genome expression profile, could be applied to model many genetic, developmental, and degenerative diseases affecting photoreceptors. It may help elucidate the molecular mechanisms underlining these diseases, drug screening of compounds with potential therapeutic effects, and predict drug side effects

Effects of dance therapy on balance, gait and neuro-psychological performances in patients with Parkinson's disease and postural instability

Postural Instability (PI) is a core feature of Parkinson’s Disease (PD) and a major cause of falls and disabilities. Impairment of executive functions has been called as an aggravating factor on motor performances. Dance therapy has been shown effective for improving gait and has been suggested as an alternative rehabilitative method. To evaluate gait performance, spatial-temporal (S-T) gait parameters and cognitive performances in a cohort of patients with PD and PI modifications in balance after a cycle of dance therapy

LDA-Based Topic Strength Analysis

Topic strength is an important hotspot in topic research. The evolution of topic strength not only indicates emerging new topics, but also helps us to determine whether a topic will produce some fluctuation of topic strength over time. Thus, topic strength analysis can provide significant findings in public opinion monitoring and user personalization. In this paper, we present an LDA-based topic strength analysis approach. We take topic quality into our topic strength consideration by combining local LDA and global LDA. For empirical studies, we use three data sets in real applications: film critic data of "A Chinese Odyssey" in Douban Movies, corruption news data in Sina News, and public paper data. Compared to existing approaches, experimental results show that our proposed approach can obtain better results of topic strength analysis in detecting the time of event topic occurrences and distinguishing different types of topics, and it can be used to monitor the occurrences of public opinions and the changes of public concerns

Aerospace Medicine and Biology: A continuing bibliography with indexes

This bibliography lists 253 reports, articles, and other documents introduced into the NASA scientific and technical information system in October 1975