The Analysis of Existing Experience for the Ethnobotanical Information System

Ethnobotanical researches reflect the conventional learning of a region. Over the previous decade, medical plants which used for healing indigenous people has become a significant notion among the people and impacted improvement of scientific and ethnobotanical knowledge and investigations of eliminating health problems. A public database has been based on data assembled from various verifiable sources, including journals, travel records, and treatises on therapeutic plants, composed by explorers, botanists, doctors, researchers who went to the nations during the most recent three centuries. In addition, ethnobotanical data depicted in chronicled natural accumulations and in Ancient and Medieval writings from the inquired district have been incorporated into the database. The databases have to be sufficiently adaptable to illustrate a valuable tool for analysts who need to store and analyze present and past ethnobotanical data from the researched location. The ethnobotanical researches are improved in Azerbaijan day by day. The database is used for informing people about some national plants which are growing in the different region of Azerbaijan. The ethnobotanical databases from different countries are analyzed in this article.There are used some special methods for comparing the differences among these databases as data mining and text mining. As a first step the suitable databases are gathered for our investigation, then are defined the best information systems that are used in many countries\u27 biologists and scientists and the end is observed advantages and disadvantages of all existing ethnobotanical databases which we researched. The features of information systems are evaluated. The results demonstrated each of databases has its very own quality, but none has turned a standard form for universal research. The reason is very basic: none of these databases enable specialists to include their own information. There is also illustrated sample structure, main tables and key components of the ethnobotanical database.The obtained results, while a few ethnobotanical databases existing, none are satisfactory answers for worldwide work, and none enable analysts to include their very own information. There is a need brought together all essential properties of existing databases, and creating a free database that encourages ethnobotanical research. Due to the rise and quick improvement in the field of data advances, it has now turned out to be conceivable to digitize, oversee and make ethnobotanical information accessible to a more extensive gathering of people

Chapter 2 - A Discussion of Methods, pp. 31-44

The Catherwood Library and ILR School at Cornell are pleased to again make available an extremely important index of major labor union publications, long out of print. It is Lloyd G. Reynolds and Charles C. Killingsworth\u27s Trade Union Publications: The Official Journals, Convention Proceedings and Constitutions of International Unions and Federations, 1850-1941. Baltimore, The John Hopkins Press, 1944

Drosophila olfactory receptors as classifiers for volatiles from disparate real world applications

Olfactory receptors evolved to provide animals with ecologically and behaviourally relevant information. The resulting extreme sensitivity and discrimination has proven useful to humans, who have therefore co-opted some animals' sense of smell. One aim of machine olfaction research is to replace the use of animal noses and one avenue of such research aims to incorporate olfactory receptors into artificial noses. Here, we investigate how well the olfactory receptors of the fruit fly, Drosophila melanogaster, perform in classifying volatile odourants that they would not normally encounter. We collected a large number of in vivo recordings from individual Drosophila olfactory receptor neurons in response to an ecologically relevant set of 36 chemicals related to wine ('wine set') and an ecologically irrelevant set of 35 chemicals related to chemical hazards ('industrial set'), each chemical at a single concentration. Resampled response sets were used to classify the chemicals against all others within each set, using a standard linear support vector machine classifier and a wrapper approach. Drosophila receptors appear highly capable of distinguishing chemicals that they have not evolved to process. In contrast to previous work with metal oxide sensors, Drosophila receptors achieved the best recognition accuracy if the outputs of all 20 receptor types were used

Computational Sociolinguistics: A Survey

Language is a social phenomenon and variation is inherent to its social nature. Recently, there has been a surge of interest within the computational linguistics (CL) community in the social dimension of language. In this article we present a survey of the emerging field of "Computational Sociolinguistics" that reflects this increased interest. We aim to provide a comprehensive overview of CL research on sociolinguistic themes, featuring topics such as the relation between language and social identity, language use in social interaction and multilingual communication. Moreover, we demonstrate the potential for synergy between the research communities involved, by showing how the large-scale data-driven methods that are widely used in CL can complement existing sociolinguistic studies, and how sociolinguistics can inform and challenge the methods and assumptions employed in CL studies. We hope to convey the possible benefits of a closer collaboration between the two communities and conclude with a discussion of open challenges.Comment: To appear in Computational Linguistics. Accepted for publication: 18th February, 201

Finding needles in haystacks: linking scientific names, reference specimens and molecular data for Fungi

DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing number of molecular ecology and microbiome projects using high-throughput sequencing require fast and effective methods for en masse species assignments. In this article, we focus on selecting and re-annotating a set of marker reference sequences that represent each currently accepted order of Fungi. The particular focus is on sequences from the internal transcribed spacer region in the nuclear ribosomal cistron, derived from type specimens and/or ex-type cultures. Re-annotated and verified sequences were deposited in a curated public database at the National Center for Biotechnology Information (NCBI), namely the RefSeq Targeted Loci (RTL) database, and will be visible during routine sequence similarity searches with NR_prefixed accession numbers. A set of standards and protocols is proposed to improve the data quality of new sequences, and we suggest how type and other reference sequences can be used to improve identification of Fungi

Using distributional similarity to organise biomedical terminology

We investigate an application of distributional similarity techniques to the problem of structural organisation of biomedical terminology. Our application domain is the relatively small GENIA corpus. Using terms that have been accurately marked-up by hand within the corpus, we consider the problem of automatically determining semantic proximity. Terminological units are dened for our purposes as normalised classes of individual terms. Syntactic analysis of the corpus data is carried out using the Pro3Gres parser and provides the data required to calculate distributional similarity using a variety of dierent measures. Evaluation is performed against a hand-crafted gold standard for this domain in the form of the GENIA ontology. We show that distributional similarity can be used to predict semantic type with a good degree of accuracy

Automatically assembling a full census of an academic field

The composition of the scientific workforce shapes the direction of scientific research, directly through the selection of questions to investigate, and indirectly through its influence on the training of future scientists. In most fields, however, complete census information is difficult to obtain, complicating efforts to study workforce dynamics and the effects of policy. This is particularly true in computer science, which lacks a single, all-encompassing directory or professional organization. A full census of computer science would serve many purposes, not the least of which is a better understanding of the trends and causes of unequal representation in computing. Previous academic census efforts have relied on narrow or biased samples, or on professional society membership rolls. A full census can be constructed directly from online departmental faculty directories, but doing so by hand is prohibitively expensive and time-consuming. Here, we introduce a topical web crawler for automating the collection of faculty information from web-based department rosters, and demonstrate the resulting system on the 205 PhD-granting computer science departments in the U.S. and Canada. This method constructs a complete census of the field within a few minutes, and achieves over 99% precision and recall. We conclude by comparing the resulting 2017 census to a hand-curated 2011 census to quantify turnover and retention in computer science, in general and for female faculty in particular, demonstrating the types of analysis made possible by automated census construction.Comment: 11 pages, 6 figures, 2 table