Journal Guide

Darwiniana is a half-yearly botanic publication of the Instituto de Botánica Darwinion, (CONICET-ANCEFN). Its mission is to publish original scientific papers and reviews from different areas of plant science with the exception of those which are agronomical or applied botanical research (of direct transfer). Main articles are usually included in the following sections: Archeobotany and Ethnobotany, Reproductive biology, Ecology and Phytogeography, Structure and Development, Genetics, Systematics and Taxonomy of Nonvascular Plants, and Systematics and Taxonomy of Vascular Plants. The Editorial Board may publish book reviews, obituaries, communications to the subscribers, and the instructions to authors in the section "Miscellany".The editing process includes 4 main succesive steps: 1) a preliminary evaluation of the article; 2) a peer review made by two or three independent reviewers not belonging to the Darwiniana Editorial Board; 3) the style corrections; and 4) correction of print proofs. .

Das Gesundheitswesen informiert Sie umfassend und aktuell über die wichtigsten Themen des Gesundheitswesens. Neben Leitlinien, Übersichten und Kommentaren werden auch aktuelle Forschungsergebnisse und Beiträge für die CME-zertifizierte Fort- und Weiterbildung publiziert. Die Zeitschrift bietet ein wissenschaftliches Diskussionsforum und eine Plattform für Mitteilungen der Fachgesellschaften

Das Neurophysiologie-Labor richtet sich vor allem an Elektrophysiologisch-Technische Assistenten in Laboratorien und Kliniken, ist aber auch fuer den Neurologen von Interesse. Zentrales Anliegen sind die Anleitung und Weiterbildung im Zusammenhang mit allen Gebieten, die fuer die taegliche Arbeit von Elektrophysiologisch-Technischen Assistenten notwendig sind. So schliesst Das Neurophysiologie-Labor die Luecke, die trotz exzellenter Kurse und Seminare, die vom Fachverband Neurophysiologisch-Technischer Assistenten e.V. geleitet werden, verbleibt.

Database Systems and Knowledgebase Systems share many common principles. Data & Knowledge Engineering (DKE) stimulates the exchange of ideas and interaction between these two related fields of interest. DKE reaches a world-wide audience of researchers, designers, managers and users. The major aim of the journal is to identify, investigate and analyze the underlying principles in the design and effective use of these systems. DKE achieves this aim by publishing original research results, technical advances and news items concerning data engineering, knowledge engineering, and the interface of these two fields.DKE covers the following topics:1. Representation and Manipulation of Data & Knowledge: Conceptual data models. Knowledge representation techniques. Data/knowledge manipulation languages and techniques.2. Architectures of database, expert, or knowledge-based systems: New architectures for database / knowledge base / expert systems, design and implementation techniques, languages and user interfaces, distributed architectures.3. Construction of data/knowledge bases: Data / knowledge base design methodologies and tools, data/knowledge acquisition methods, integrity/security/maintenance issues.4. Applications, case studies, and management issues: Data administration issues, knowledge engineering practice, office and engineering applications.5. Tools for specifying and developing Data and Knowledge Bases using tools based on Linguistics or Human Machine Interface principles.6. Communication aspects involved in implementing, designing and using KBSs in Cyberspace.Plus... conference reports, calendar of events, book reviews etc.Benefits to authorsWe also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our support pages: http://support.elsevier.com

The premier technical publication in the field, Data Mining and Knowledge Discovery is a resource collecting relevant common methods and techniques and a forum for unifying the diverse constituent research communities. The journal publishes original technical papers in both the research and practice of data mining and knowledge discovery, surveys and tutorials of important areas and techniques, and detailed descriptions of significant applications. Coverage includes: - Theory and Foundational Issues - Data Mining Methods - Algorithms for Data Mining - Knowledge Discovery Process - Application Issues.

The CODATA Data Science Journal is a peer-reviewed, open access, electronic journal, publishing papers on the management, dissemination, use and reuse of research data and databases across all research domains, including science, technology, the humanities and the arts. The scope of the journal includes descriptions of data systems, their implementations and their publication, applications, infrastructures, software, legal, reproducibility and transparency issues, the availability and usability of complex datasets, and with a particular focus on the principles, policies and practices for open data.

All data is in scope, whether born digital or converted from other sources.