Collaborative Requirements Engineering Notation for Planning Globally Distributed Projects

Requirements engineering represents a critical phase of the software development lifecycle in which requirements describing the functional and non-functional behaviors of a system are elicited, modeled, analyzed, negotiated, agreed, and specified. In traditional software systems these tasks are typically performed in face-to-face meetings between requirements engineers and the project level stakeholders. However, in today’s global software development environment, it is becoming increasingly commonplace for stakeholders to be dispersed across multiple geographical locations and time zones. Under these circumstances, face-to-face meetings become expensive, and often impossible to facilitate, and as a result the success of the requirements process relies, at least partially, on tools and processes that support distributed communication and collaboration. To investigate the challenges and effective practices for performing requirements activities in distributed environments, we conducted a series of in-depth interviews with project managers and business analysts who have worked with non-co-located stakeholders. Since many project managers fail to plan and deploy the necessary infrastructures to support quality communication, and in practice requirements are often elicited and managed via email exchanges; we introduced a visual modeling notation to help project managers proactively plan the collaboration infrastructures needed to support requirements-related activities in globally distributed projects. An underlying meta-model defines the elements of the modeling language, including locations, stakeholder roles, communication flows, critical documents, and supporting tools and repositories. The interview findings were further analyzed to identify practices that led to success or created significant challenges for the projects; resulting in a set of patterns for globally distributed requirements engineering

Perspectives on Tobacco Product Waste: A Survey of Framework Convention Alliance Members' Knowledge, Attitudes, and Beliefs.

Cigarette butts (tobacco product waste (TPW)) are the single most collected item in environmental trash cleanups worldwide. This brief descriptive study used an online survey tool (Survey Monkey) to assess knowledge, attitudes, and beliefs among individuals representing the Framework Convention Alliance (FCA) about this issue. The FCA has about 350 members, including mainly non-governmental tobacco control advocacy groups that support implementation of the World Health Organization's (WHO) Framework Convention on Tobacco Control (FCTC). Although the response rate (28%) was low, respondents represented countries from all six WHO regions. The majority (62%) have heard the term TPW, and nearly all (99%) considered TPW as an environmental harm. Most (77%) indicated that the tobacco industry should be responsible for TPW mitigation, and 72% felt that smokers should also be held responsible. This baseline information may inform future international discussions by the FCTC Conference of the Parties (COP) regarding environmental policies that may be addressed within FCTC obligations. Additional research is planned regarding the entire lifecycle of tobacco's impact on the environment

Motion clouds: model-based stimulus synthesis of natural-like random textures for the study of motion perception

Choosing an appropriate set of stimuli is essential to characterize the response of a sensory system to a particular functional dimension, such as the eye movement following the motion of a visual scene. Here, we describe a framework to generate random texture movies with controlled information content, i.e., Motion Clouds. These stimuli are defined using a generative model that is based on controlled experimental parametrization. We show that Motion Clouds correspond to dense mixing of localized moving gratings with random positions. Their global envelope is similar to natural-like stimulation with an approximate full-field translation corresponding to a retinal slip. We describe the construction of these stimuli mathematically and propose an open-source Python-based implementation. Examples of the use of this framework are shown. We also propose extensions to other modalities such as color vision, touch, and audition

Comparison of reproducibility, accuracy, sensitivity, and specificity of miRNA quantification platforms

Given the increasing interest in their use as disease biomarkers, the establishment of reproducible, accurate, sensitive, and specific platforms for microRNA (miRNA) quantification in biofluids is of high priority. We compare four platforms for these characteristics: small RNA sequencing (RNA-seq), FirePlex, EdgeSeq, and nCounter. For a pool of synthetic miRNAs, coefficients of variation for technical replicates are lower for EdgeSeq (6.9%) and RNA-seq (8.2%) than for FirePlex (22.4%); nCounter replicates are not performed. Receiver operating characteristic analysis for distinguishing present versus absent miRNAs shows small RNA-seq (area under curve 0.99) is superior to EdgeSeq (0.97), nCounter (0.94), and FirePlex (0.81). Expected differences in expression of placenta-associated miRNAs in plasma from pregnant and non-pregnant women are observed with RNA-seq and EdgeSeq, but not FirePlex or nCounter. These results indicate that differences in performance among miRNA profiling platforms impact ability to detect biological differences among samples and thus their relative utility for research and clinical use