Automated Detection of Usage Errors in non-native English Writing

In an investigation of the use of a novelty detection algorithm for identifying inappropriate word combinations in a raw English corpus, we employ an unsupervised detection algorithm based on the one- class support vector machines (OC-SVMs) and extract sentences containing word sequences whose frequency of appearance is significantly low in native English writing. Combined with n-gram language models and document categorization techniques, the OC-SVM classifier assigns given sentences into two different groups; the sentences containing errors and those without errors. Accuracies are 79.30 % with bigram model, 86.63 % with trigram model, and 34.34 % with four-gram model

Riccati differential equations with elliptic coefficients II

We study a Riccati differential equation whose coefficient is expressible in terms of a special Weierstrass pe-function. We show that all the solutions are meromorphic, and examine the periodicity of them.We study a Riccati differential equation whose coefficient is expressible in terms of a special Weierstrass pe-function. We show that all the solutions are meromorphic, and examine the periodicity of them

Network Features and Pathway Analyses of a Signal Transduction Cascade

The scale-free and small-world network models reflect the functional units of networks. However, when we investigated the network properties of a signaling pathway using these models, no significant differences were found between the original undirected graphs and the graphs in which inactive proteins were eliminated from the gene expression data. We analyzed signaling networks by focusing on those pathways that best reflected cellular function. Therefore, our analysis of pathways started from the ligands and progressed to transcription factors and cytoskeletal proteins. We employed the Python module to assess the target network. This involved comparing the original and restricted signaling cascades as a directed graph using microarray gene expression profiles of late onset Alzheimer's disease. The most commonly used method of shortest-path analysis neglects to consider the influences of alternative pathways that can affect the activation of transcription factors or cytoskeletal proteins. We therefore introduced included k-shortest paths and k-cycles in our network analysis using the Python modules, which allowed us to attain a reasonable computational time and identify k-shortest paths. This technique reflected results found in vivo and identified pathways not found when shortest path or degree analysis was applied. Our module enabled us to comprehensively analyse the characteristics of biomolecular networks and also enabled analysis of the effects of diseases considering the feedback loop and feedforward loop control structures as an alternative path

The Naming of Names: Guidelines for Gene Nomenclature in Marchantia.

While Marchantia polymorpha has been utilized as a model system to investigate fundamental biological questions for over almost two centuries, there is renewed interest in M. polymorpha as a model genetic organism in the genomics era. Here we outline community guidelines for M. polymorpha gene and transgene nomenclature, and we anticipate that these guidelines will promote consistency and reduce both redundancy and confusion in the scientific literature

Insights into Land Plant Evolution Garnered from the Marchantia polymorpha Genome.

The evolution of land flora transformed the terrestrial environment. Land plants evolved from an ancestral charophycean alga from which they inherited developmental, biochemical, and cell biological attributes. Additional biochemical and physiological adaptations to land, and a life cycle with an alternation between multicellular haploid and diploid generations that facilitated efficient dispersal of desiccation tolerant spores, evolved in the ancestral land plant. We analyzed the genome of the liverwort Marchantia polymorpha, a member of a basal land plant lineage. Relative to charophycean algae, land plant genomes are characterized by genes encoding novel biochemical pathways, new phytohormone signaling pathways (notably auxin), expanded repertoires of signaling pathways, and increased diversity in some transcription factor families. Compared with other sequenced land plants, M. polymorpha exhibits low genetic redundancy in most regulatory pathways, with this portion of its genome resembling that predicted for the ancestral land plant. PAPERCLIP

Important Sentence Extraction Using Contextual Semantic Network

AbstractIn this paper, we propose a method for calculating important scores of sentences for text summarization. In this method, Contextual Semantic Network is used to calculate scores of importance for sentences included in input documents. The Contextual Semantic Network is constructed by using the Associative Concept Dictionary which includes semantic relations and distance information among the words in the documents. The concept dictionary was built using the results of association experiments which adopted basic nouns as stimulus words in Japanese elementary school textbooks. For evaluating the method, we compared the quality of the important score ranking obtained from our proposed method with that obtained from human subjects and that obtained from a conventional method using term frequency (tfidf). We used eight documents from the Japanese textbooks for the evaluation and carried out an experiment where 40 human subjects chose the five most important sentences from each of the eight documents. The results show that summarization accuracy can be improved by applying our method

Neural Coding Model Using the Morphoelectrotonic Transform Theory

It is believed that the color and the shape movement etc. of objects are expressed with time series of neuron spikes in the brain. We do not have any answer to realize the process, “What kind of neuron dynamics works and is able to express the processes? ” To solve this problem, we need at least to study the neural coding where information is expressed by the spike sequence