Social Media in Transparent Work Environments

Abstract-Social media is being integrated into work environments making them more transparent. When the work environment is transparent, it has the potential to allow projects to transmit information about work artifacts and events quickly through a large network. Using signaling theory, we propose a theory that users interpret this information and then make workrelated decisions about attention and effort allocation in a principled manner. In our research setting, an open source context of voluntary participation, broadcast activity information act as signals that allow developers to make highly informed choices about where to expend their attention and effort and with whom to collaborate. We propose four potential signals from literature and interviews with developers in our research setting and discuss the implications for social media in software development environments

The Cloud Absorption Radiometer HDF Data User's Guide

The purpose of this document is to describe the Cloud Absorption Radiometer (CAR) Instrument, methods used in the CAR Hierarchical Data Format (HDF) data processing, the structure and format of the CAR HDF data files, and methods for accessing the data. Examples of CAR applications and their results are also presented. The CAR instrument is a multiwavelength scanning radiometer that measures the angular distributions of scattered radiation

The Saharan Air Layer and the Fate of African Easterly Waves—NASA's AMMA Field Study of Tropical Cyclogenesis

In 2006, NASA led a field campaign to investigate the factors that control the fate of African easterly waves (AEWs) moving westward into the tropical Atlantic Ocean. Aircraft and surface-based equipment were based on Cape Verde's islands, helping to fill some of the data void between Africa and the Caribbean. Taking advantage of the international African Monsoon Multidisciplinary Analysis (AMMA) program over the continent, the NASA–AMMA (NAMMA) program used enhanced upstream data, whereas NOAA aircraft farther west in the Atlantic studied several of the storms downstream. Seven AEWs were studied during AMMA, with at least two becoming tropical cyclones. Some of the waves that did not develop while being sampled near Cape Verde likely intensified in the central Atlantic instead. NAMMA observations were able to distinguish between the large-scale wave structure and the smaller-scale vorticity maxima that often form within the waves. A special complication of the east Atlantic environment is the Saharan air layer (SAL), which frequently accompanies the AEWs and may introduce dry air and heavy aerosol loading into the convective storm systems in the AEWs. One of the main achievements of NAMMA was the acquisition of a database of remote sensing and in situ observations of the properties of the SAL, enabling dynamic models and satellite retrieval algorithms to be evaluated against high-quality real data. Ongoing research with this database will help determine how the SAL influences cloud micro-physics and perhaps also tropical cyclogenesis, as well as the more general question of recognizing the properties of small-scale vorticity maxima within tropical waves that are more likely to become tropical cyclones

Expanding the diversity of mycobacteriophages: insights into genome architecture and evolution.

Mycobacteriophages are viruses that infect mycobacterial hosts such as Mycobacterium smegmatis and Mycobacterium tuberculosis. All mycobacteriophages characterized to date are dsDNA tailed phages, and have either siphoviral or myoviral morphotypes. However, their genetic diversity is considerable, and although sixty-two genomes have been sequenced and comparatively analyzed, these likely represent only a small portion of the diversity of the mycobacteriophage population at large. Here we report the isolation, sequencing and comparative genomic analysis of 18 new mycobacteriophages isolated from geographically distinct locations within the United States. Although no clear correlation between location and genome type can be discerned, these genomes expand our knowledge of mycobacteriophage diversity and enhance our understanding of the roles of mobile elements in viral evolution. Expansion of the number of mycobacteriophages grouped within Cluster A provides insights into the basis of immune specificity in these temperate phages, and we also describe a novel example of apparent immunity theft. The isolation and genomic analysis of bacteriophages by freshman college students provides an example of an authentic research experience for novice scientists

Drying colloidal systems: laboratory models for a wide range of applications

The drying of complex fluids provides a powerful insight into phenomena that take place on time and length scales not normally accessible. An important feature of complex fluids, colloidal dispersions and polymer solutions is their high sensitivity to weak external actions. Thus, the drying of complex fluids involves a large number of physical and chemical processes. The scope of this review is the capacity to tune such systems to reproduce and explore specific properties in a physics laboratory. A wide variety of systems are presented, ranging from functional coatings, food science, cosmetology, medical diagnostics and forensics to geophysics and art

Software Developers Using Signals in Transparent Environments

<p>One of the main challenges that modern software developers face is the coordination of dependent agents such as software projects and other developers. Transparent development environments that make low-level software development activities visible hold much promise for assisting developers in making coordination decisions. However, the wealth of information that transparent environments provide is potentially overwhelming when developers are wading through information from potentially millions of developers and millions of software repositories when making decisions around tasks that require coordination with projects or other developers. Overcoming the risk of overload and better assisting developers in these environments requires a principled understanding of what exactly developers need to know about dependencies to make their decisions. My approach to a principled understanding of how developers use information in transparent environments is to model the process using signaling theory as a theoretical lens. Developers making key coordination decisions often must determine qualities about projects and other developers that are not directly observable. Developers infer these unobservable qualities through interpreting information in their environment as signals and use this judgment about the project or developer to inform their decision. In contrast to current software engineering literature which focuses on technical coordination between modules or within projects such as modularity or task assignment mechanisms, this work aims to understand how developers use signals to information coordination decisions with dependencies such as other projects or developers. Through this understanding of the signaling process, I can create improved signals that more accurately represent desired unobservable qualities. My dissertation work examines the qualities and signals that developers use to inform specific coordination tasks through a series of three empirical studies. The specific key coordination tasks studied are evaluating code contributions, discussing problems around contributions, and evaluating projects. My results suggest that when project managers evaluate code contributions, they prefer social signals over technical signals. When project managers discuss contributions, I found that they attend to political signals regarding influence from stakeholders to prioritize which problems need solutions. I found that developers evaluating projects tend to use signals that are related to how the core team works and the potential utility a project provides. In a fourth study, using signaling theory and findings from the qualities and signals that developers use to evaluate projects, I create and evaluate an improved signal called “supportiveness” for community support in projects. I compare this signal against the current signal that developers use, stars count, and find evidence suggesting that my designed signal is more robust and is a stronger indicator of support. The findings of these studies inform the design of tools and environments that assist developers in coordination tasks through suggestions of what signals to show and potentially improving existing signals. My thesis as a whole also suggests opportunities for exploring useful signals for other coordination tasks or even in different transparent environments.</p

Automatically Debugging AutoML Pipelines using Maro: ML Automated Remediation Oracle (Extended Version)

Machine learning in practice often involves complex pipelines for data cleansing, feature engineering, preprocessing, and prediction. These pipelines are composed of operators, which have to be correctly connected and whose hyperparameters must be correctly configured. Unfortunately, it is quite common for certain combinations of datasets, operators, or hyperparameters to cause failures. Diagnosing and fixing those failures is tedious and error-prone and can seriously derail a data scientist's workflow. This paper describes an approach for automatically debugging an ML pipeline, explaining the failures, and producing a remediation. We implemented our approach, which builds on a combination of AutoML and SMT, in a tool called Maro. Maro works seamlessly with the familiar data science ecosystem including Python, Jupyter notebooks, scikit-learn, and AutoML tools such as Hyperopt. We empirically evaluate our tool and find that for most cases, a single remediation automatically fixes errors, produces no additional faults, and does not significantly impact optimal accuracy nor time to convergence.Comment: Extended version of MAPS 2022 pape