Self-adaptive GA, quantitative semantic similarity measures and ontology-based text clustering

As the common clustering algorithms use vector space model (VSM) to represent document, the conceptual relationships between related terms which do not co-occur literally are ignored. A genetic algorithm-based clustering technique, named GA clustering, in conjunction with ontology is proposed in this article to overcome this problem. In general, the ontology measures can be partitioned into two categories: thesaurus-based methods and corpus-based methods. We take advantage of the hierarchical structure and the broad coverage taxonomy of Wordnet as the thesaurus-based ontology. However, the corpus-based method is rather complicated to handle in practical application. We propose a transformed latent semantic analysis (LSA) model as the corpus-based method in this paper. Moreover, two hybrid strategies, the combinations of the various similarity measures, are implemented in the clustering experiments. The results show that our GA clustering algorithm, in conjunction with the thesaurus-based and the LSA-based method, apparently outperforms that with other similarity measures. Moreover, the superiority of the GA clustering algorithm proposed over the commonly used k-means algorithm and the standard GA is demonstrated by the improvements of the clustering performance

Self-adaptive GA, quantitative semantic similarity measures and ontology-based text clustering

As the common clustering algorithms use vector space model (VSM) to represent document, the conceptual relationships between related terms which do not co-occur literally are ignored. A genetic algorithm-based clustering technique, named GA clustering, in conjunction with ontology is proposed in this article to overcome this problem. In general, the ontology measures can be partitioned into two categories: thesaurus-based methods and corpus-based methods. We take advantage of the hierarchical structure and the broad coverage taxonomy of Wordnet as the thesaurus-based ontology. However, the corpus-based method is rather complicated to handle in practical application. We propose a transformed latent semantic analysis (LSA) model as the corpus-based method in this paper. Moreover, two hybrid strategies, the combinations of the various similarity measures, are implemented in the clustering experiments. The results show that our GA clustering algorithm, in conjunction with the thesaurus-based and the LSA-based method, apparently outperforms that with other similarity measures. Moreover, the superiority of the GA clustering algorithm proposed over the commonly used k-means algorithm and the standard GA is demonstrated by the improvements of the clustering performance

Mice Exposed to Chronic Intermittent Hypoxia Simulate Clinical Features of Deficiency of both Qi and Yin Syndrome in Traditional Chinese Medicine

Deficiency of both Qi and Yin Syndrome (DQYS) is one of the common syndromes in traditional Chinese medicine (TCM), mainly characterized by tiredness, emaciation, anorexia, fidget, palpitation and rapid pulse, and so forth. Currently, there is no available animal model which can reflect the clinical features of this syndrome. In the present paper, we observed the time-course changes of whole behavior, body weight, food intake, locomotive activity and electrocardiogram in mice exposed to chronic intermittent hypoxia for 6 weeks, and measured bleeding time at last according to the clinical features of DQYS and one key pathological factor. The results showed that the mice exposed to intermittent hypoxia for certain time presented lackluster hair, dull looking hair, resistance, attacking, body weight loss, food intake decline, locomotive activity decrease, heart rate quickening and T wave elevating, which were similar to the major clinical features of DQYS. Meanwhile, bleeding time shortening was also found, which was consistent with the clinical fact that DQYS often accompanied with blood stasis. The possible explanation was also outlined according to the available literature. Such findings suggested chronic intermittent hypoxia could induce similar symptoms and signs in mice accorded with the clinical features of DQYS, which provided a suitable animal model for evaluation of drugs for the treatment of this syndrome and further exploration of pathological process or correlation of the syndrome and related diseases

Ultra-Conformal Skin Electrodes With Synergistically Enhanced Conductivity For Long-Time and Low-Motion Artifact Epidermal Electrophysiology

Accurate and imperceptible monitoring of electrophysiological signals is of primary importance for wearable healthcare. Stiff and bulky pregelled electrodes are now commonly used in clinical diagnosis, causing severe discomfort to users for long-time using as well as artifact signals in motion. Here, we report a ~100 nm ultra-thin dry epidermal electrode that is able to conformably adhere to skin and accurately measure electrophysiological signals. It showed low sheet resistance (~24 Ω/sq, 4142 S/cm), high transparency, and mechano-electrical stability. The enhanced optoelectronic performance was due to the synergistic effect between graphene and poly (3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS), which induced a high degree of molecular ordering on PEDOT and charge transfer on graphene by strong π-π interaction. Together with ultra-thin nature, this dry epidermal electrode is able to accurately monitor electrophysiological signals such as facial skin and brain activity with low-motion artifact, enabling human-machine interfacing and long-time mental/physical health monitoring

Types of Tags for Annotating Academic Blogs

Academic blog sites are popular academic information exchange platforms, and they have been widely used in recent years. Blogs in those sites are often annotated with tags, and the tags can help to describe, organize and retrieve these blogs. However, it is still unknown what types of tags are frequently adopted for annotating academic blogs. In this poster, we present survey results for detecting the usage of tag types, and its changes with the bloggers' demographic information. We believe that our study can benefit users in their access to academic blogs and help the academic blog websites improve their services

Specific biomarker mining and rapid detection of Burkholderia cepacia complex by recombinase polymerase amplification

ObjectiveTo mine specific proteins and their protein-coding genes as suitable molecular biomarkers for the Burkholderia cepacia Complex (BCC) bacteria detection based on mega analysis of microbial proteomic and genomic data comparisons and to develop a real-time recombinase polymerase amplification (rt-RPA) assay for rapid isothermal screening for pharmaceutical and personal care products.MethodsWe constructed an automatic screening framework based on Python to compare the microbial proteomes of 78 BCC strains and 263 non-BCC strains to identify BCC-specific protein sequences. In addition, the specific protein-coding gene and its core DNA sequence were validated in silico with a self-built genome database containing 158 thousand bacteria. The appropriate methodology for BCC detection using rt-RPA was evaluated by 58 strains in pure culture and 33 batches of artificially contaminated pharmaceutical and personal care products.ResultsWe identified the protein SecY and its protein-coding gene secY through the automatic comparison framework. The virtual evaluation of the conserved region of the secY gene showed more than 99.8% specificity from the genome database, and it can distinguish all known BCC species from other bacteria by phylogenetic analysis. Furthermore, the detection limit of the rt-RPA assay targeting the secY gene was 5.6 × 102 CFU of BCC bacteria in pure culture or 1.2 pg of BCC bacteria genomic DNA within 30 min. It was validated to detect <1 CFU/portion of BCC bacteria from artificially contaminated samples after a pre-enrichment process. The relative trueness and sensitivity of the rt-RPA assay were 100% in practice compared to the reference methods.ConclusionThe automatic comparison framework for molecular biomarker mining is straightforward, universal, applicable, and efficient. Based on recognizing the BCC-specific protein SecY and its gene, we successfully established the rt-RPA assay for rapid detection in pharmaceutical and personal care products