Increased variability of microbial communities in restored salt marshes nearly 30 years after tidal flow restoration

We analyzed microbial diversity and community composition from four salt marsh sites that were impounded for 40–50 years and subsequently restored and four unimpounded sites in southeastern Connecticut over one growing season. Community composition and diversity were assessed by terminal restriction fragment length polymorphism (TRFLP) and sequence analysis of 16S ribosomal RNA (rRNA) genes. Our results indicated diverse communities, with sequences representing 14 different bacterial divisions. Proteobacteria, Bacteroidetes, and Planctomycetes dominated clone libraries from both restored and unimpounded sites. Multivariate analysis of the TRFLP data suggest significant site, sample date, and restoration status effects, but the exact causes of these effects are not clear. Composition of clone libraries and abundance of bacterial 16S rRNA genes were not significantly different between restored sites and unimpounded sites, but restored sites showed greater temporal and spatial variability of bacterial communities based on TRFLP profiles compared with unimpounded sites, and variability was greatest at sites more recently restored. In summary, our study suggests there may be long-lasting effects on stability of bacterial communities in restored salt marshes and raises questions about the resilience and ultimate recovery of the communities after chronic disturbance

Empirical Evidence of Large-Scale Diversity in API Usage of Object-Oriented Software

In this paper, we study how object-oriented classes are used across thousands of software packages. We concentrate on "usage diversity'", defined as the different statically observable combinations of methods called on the same object. We present empirical evidence that there is a significant usage diversity for many classes. For instance, we observe in our dataset that Java's String is used in 2460 manners. We discuss the reasons of this observed diversity and the consequences on software engineering knowledge and research

A systematic review of software development cost estimation studies

This paper aims to provide a basis for the improvement of software estimation research through a systematic review of previous work. The review identifies 304 software cost estimation papers in 76 journals and classifies the papers according to research topic, estimation approach, research approach, study context and data set. A web-based library of these cost estimation papers is provided to ease the identification of relevant estimation research results. The review results combined with other knowledge provide support for recommendations for future software cost estimation research, including: 1) Increase the breadth of the search for relevant studies, 2) Search manually for relevant papers within a carefully selected set of journals when completeness is essential, 3) Conduct more studies on estimation methods commonly used by the software industry, and, 4) Increase the awareness of how properties of the data sets impact the results when evaluating estimation methods

A Review of Theory and Practice in Scientometrics

Scientometrics is the study of the quantitative aspects of the process of science as a communication system. It is centrally, but not only, concerned with the analysis of citations in the academic literature. In recent years it has come to play a major role in the measurement and evaluation of research performance. In this review we consider: the historical development of scientometrics, sources of citation data, citation metrics and the “laws" of scientometrics, normalisation, journal impact factors and other journal metrics, visualising and mapping science, evaluation and policy, and future developments

Performance Portability Through Semi-explicit Placement in Distributed Erlang

We consider the problem of adapting distributed Erlang applications to large or heterogeneous architectures to achieve good performance in a portable way. In many architectures, and especially large architectures, the communication latency between pairs of virtual machines (nodes) is no longer uniform. We propose two language-level methods that enable programs to automatically adapt to heterogeneity and non-uniform communication latencies, and both provide information enabling a program to identify an appropriate node when spawning a process. We provide a means of recording node attributes describing the hardware and software capabilities of nodes, and mechanisms that allow an application to examine the attributes of remote nodes. We provide an abstraction of communication distances that enables an application to select nodes to facilitate efficient communication. We have developed open source libraries that implement these ideas. We show that the use of attributes for node selection can lead to significant performance improvements if different components of the application have different processing requirements. We report a detailed empirical investigation of non-uniform communication times in several representative architectures, and show that our abstract model provides a good description of the hierarchy of communication times