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The paper introduces a visual programming language and corresponding web and cloud-based development environment called NetsBlox. NetsBlox is an extension of Snap! and builds upon its visual formalism as well as its open source code base. NetsBlox adds distributed programming capabilities by introducing two well-known abstractions to block-based programming: message passing and Remote Procedure Calls (RPC). Messages containing data can be exchanged by two or more NetsBlox programs running on different computers connected to the Internet. RPCs are called on a client program and are executed on the NetsBlox server. These two abstractions make it possible to create distributed programs such as multi-player games or client–server applications. We believe that NetsBlox not only teaches basic distributed programming concepts but also provides increased motivation for high-school students to become creators and not just consumers of technology. [ABSTRACT FROM AUTHOR]

Distributed computing, computer networking, and the Internet of Things (IoT) are all around us, yet only computer science and engineering majors learn the technologies that enable our modern lives. This paper introduces PhoneIoT, a mobile app that makes it possible to teach some of the basic concepts of distributed computation and networked sensing to novices. PhoneIoT turns mobile phones and tablets into IoT devices and makes it possible to create highly engaging projects through NetsBlox, an open-source block-based programming environment focused on teaching distributed computing at the high school level. PhoneIoT lets NetsBlox programs—running in the browser on the student's computer—access available sensors. Since phones have touchscreens, PhoneIoT also allows building a Graphical User Interface (GUI) remotely from NetsBlox, which can be set to trigger custom code written by the student via NetsBlox's message system. This approach enables students to create quite advanced distributed projects, such as turning their phone into a game controller or tracking their exercise on top of an interactive Google Maps background with just a few blocks of code. [ABSTRACT FROM AUTHOR]

Many diseases linked with ethnic health disparities associate with changes in microbial communities in the United States, but the causes and persistence of ethnicity-associated microbiome variation are not understood. For instance, microbiome studies that strictly control for diet across ethnically diverse populations are lacking. Here, we performed multiomic profiling over a 9-day period that included a 4-day controlled vegetarian diet intervention in a defined geographic location across 36 healthy Black and White females of similar age, weight, habitual diets, and health status. We demonstrate that individuality and ethnicity account for roughly 70% to 88% and 2% to 10% of taxonomic variation, respectively, eclipsing the effects a short-term diet intervention in shaping gut and oral microbiomes and gut viromes. Persistent variation between ethnicities occurs for microbial and viral taxa and various metagenomic functions, including several gut KEGG orthologs, oral carbohydrate active enzyme categories, cluster of orthologous groups of proteins, and antibiotic-resistant gene categories. In contrast to the gut and oral microbiome data, the urine and plasma metabolites tend to decouple from ethnicity and more strongly associate with diet. These longitudinal, multiomic profiles paired with a dietary intervention illuminate previously unrecognized associations of ethnicity with metagenomic and viromic features across body sites and cohorts within a single geographic location, highlighting the importance of accounting for human microbiome variation in research, health determinants, and eventual therapies. Trial Registration: ClinicalTrials.gov ClinicalTrials.gov Identifier: NCT03314194. Many diseases linked with ethnic health disparities associate with changes in microbial communities in the United States, but the causes and persistence of ethnicity-associated microbiome variation are not understood. This study reveals that individuality and ethnicity eclipse a short-term dietary intervention in shaping microbiomes and viromes. [ABSTRACT FROM AUTHOR]

The paper introduces DeepForge, a gateway to deep learning for scientific computing. DeepForge provides an easy to use, yet powerful visual/textual interface to facilitate the rapid development of deep learning models by novices as well as experts. Utilizing a cloud-based infrastructure, built-in version control, and multiuser collaboration support, DeepForge promotes reproducibility and ease of access and enables remote execution of machine learning pipelines. The tool currently supports TensorFlow/Keras, but its extensible architecture enables easy integration of additional platforms. [ABSTRACT FROM AUTHOR]

Synergistic learning combining computational thinking (CT) and STEM has proven to be an effective method for advancing learning and understanding in a number of STEM domains and simultaneously helping students develop important CT concepts and practices. We adopt a design-based approach to develop, evaluate, and refine our Collaborative, Computational STEM (C2STEM) learning environment. The system adopts a novel paradigm that combines visual model building with a domain-specific modeling language (DSML) to scaffold learning of high school physics using a computational modeling approach. In this paper, we discuss the design principles that guided the development of our open-ended learning environment (OELE) using a learning-by-modeling and evidence-centered approach for curriculum and assessment design. Students learn by building models that describe the motion of objects, and their learning is supported by scaffolded tasks and embedded formative assessments that introduce them to physics and CT concepts. We have also developed preparation for future learning (PFL) assessments to study students' abilities to generalize and apply CT and science concepts and practices across problem solving tasks and domains. We use mixed quantitative and qualitative analysis methods to analyze student learning during a semester-long study run in a high school physics classroom. We document some of the lessons learned from this study and discuss directions for future work. [ABSTRACT FROM AUTHOR]

In a two-wave, 4-month longitudinal study of 308 adults, two hypotheses were tested regarding the relation of Twitter-based measures of online social media use and in-person social support with depressive thoughts and symptoms. For four of five measures, Twitter use by in-person social support interactions predicted residualized change in depression-related outcomes over time; these results supported a corollary of the social compensation hypothesis that social media use is associated with greater benefits for people with lower in-person social support. In particular, having a larger Twitter social network (i.e., following and being followed by more people) and being more active in that network (i.e., sending and receiving more tweets) are especially helpful to people who have lower levels of in-person social support. For the fifth measure (the sentiment of Tweets), no interaction emerged; however, a beneficial main effect offset the adverse main effect of low in-person social support. [ABSTRACT FROM AUTHOR]

Since the introduction of Wireless Capsule Endoscopy (WCE) researchers have started exploring the design space of Medical Capsule Robots (MCRs): embedded micro-systems that can operate autonomously within the human body and can diagnose, prevent, monitor, and cure diseases. Although the research in the area of MCRs is an active topic and has grown exponentially, current devices provide only limited functionalities because their design process is expensive and time consuming. To open this research field to a wider community and, at the same time, create better designs through advanced tool support, in our previous works we presented a design environment for the rapid development of MCRs. In this paper, this environment was adopted to design a Drug Delivery Capsule (DDC) based on a coil-magnet-piston mechanism. The force of the coil acting on the magnetic piston and the drug release profile were modeled and assessed on bench-top with a maximum relative error below 5%. Then, in vivo trials were performed to validate the DDC functionality with a scheduled drug release profile for a 5 h and 24 min procedure. The resulting design environment template is available open source for further development of drug delivery applications as well as to serve as guideline in prototyping novel MCRs addressing other clinical needs. [ABSTRACT FROM AUTHOR]