Context-Aware Notebook Search in a Jupyter-Based Virtual Research Environment

Computational notebook environments such as the Jupyter play an increasingly important role in data-centric research for prototyping computational experiments, documenting code implementations, and sharing scientific results. Effectively discovering and reusing notebooks available on the web can reduce repetitive work and facilitate scientific innovations. However, general-purpose web search engines (e.g., Google Search) do not explicitly index the contents of notebooks, and notebook repositories (e.g., Kaggle and GitHub) require users to create domain-specific queries based on the metadata in the notebook catalogs, which fail to capture the working contexts in the notebook environment. This poster presents a Context-aware Notebook Search Framework (CANSF) to enable a researcher to seamlessly discover external notebooks based on semantic contexts of the literate programming activities in the Jupyter environment.Non

Notebook-as-a-VRE (NaaVRE): From private notebooks to a collaborative cloud virtual research environment

Virtual Research Environments (VREs) provide user-centric support in the lifecycle of research activities, e.g., discovering and accessing research assets, or composing and executing application workflows. A typical VRE is often implemented as an integrated environment, which includes a catalog of research assets, a workflow management system, a data management framework, and tools for enabling collaboration among users. Notebook environments, such as Jupyter, allow researchers to rapidly prototype scientific code and share their experiments as online accessible notebooks. Jupyter can support several popular languages that are used by data scientists, such as Python, R, and Julia. However, such notebook environments do not have seamless support for running heavy computations on remote infrastructure or finding and accessing software code inside notebooks. This paper investigates the gap between a notebook environment and a VRE and proposes an embedded VRE solution for the Jupyter environment called Notebook-as-a-VRE (NaaVRE). The NaaVRE solution provides functional components via a component marketplace and allows users to create a customized VRE on top of the Jupyter environment. From the VRE, a user can search research assets (data, software, and algorithms), compose workflows, manage the lifecycle of an experiment, and share the results among users in the community. We demonstrate how such a solution can enhance a legacy workflow that uses Light Detection and Ranging (LiDAR) data from country-wide airborne laser scanning surveys for deriving geospatial data products of ecosystem structure at high resolution over broad spatial extents. This enables users to scale out the processing of multi-terabyte LiDAR point clouds for ecological applications to more data sources in a distributed cloud environment.Comment: A revised version has been published in the journal software practice and experienc

The relationship between a plant-based diet and mental health: Evidence from a cross-sectional multicentric community trial (LIPOKAP study)

BACKGROUND: Dietary patterns emphasizing plant foods might be neuroprotective and exert health benefits on mental health. However, there is a paucity of evidence on the association between a plant-based dietary index and mental health measures. OBJECTIVE: This study sought to examine the association between plant-based dietary indices, depression and anxiety in a large multicentric sample of Iranian adults. METHODS: This cross-sectional study was performed in a sample of 2,033 participants. A validated food frequency questionnaire was used to evaluate dietary intakes of participants. Three versions of PDI including an overall PDI, a healthy PDI (hPDI), and an unhealthy PDI (uPDI) were created. The presence of anxiety and depression was examined via a validated Iranian version of the Hospital Anxiety and Depression Scale (HADS). RESULTS: PDI and hPDI were not associated to depression and anxiety after adjustment for potential covariates (age, sex, energy, marital status, physical activity level and smoking). However, in the crude model, the highest consumption of uPDI approximately doubled the risk of depression (OR= 2.07, 95% CI: 1.49, 2.87; P<0.0001) and increased the risk of anxiety by almost 50% (OR= 1.56, 95% CI: 1.14, 2.14; P= 0.001). Adjustment for potential confounders just slightly changed the associations (OR for depression in the fourth quartile= 1.96; 95% CI: 1.34, 2.85, and OR for anxiety in the fourth quartile= 1.53; 95% CI: 1.07, 2.19). CONCLUSIONS: An unhealthy plant-based dietary index is associated with a higher risk of depression and anxiety, while plant-based dietary index and healthy plant-based dietary index were not associated to depression and anxiety

Acoustical Excitation for Damping Estimation in Rotating Machinery

In experimental modal analysis a structure is excited with a force in order to estimate the frequency response function. Typically, this force is generated by a shaker or a hammer impact. Both methods have proven their usefulness, but have some well-known disadvantages. A main disadvantage of the shaker is that it has to be fixed to the structure whereas with a hammer it is not possible to excite a specific frequency. To overcome these disadvantages, alternative non-contact methods can be used. There are several non-contact techniques, i.e. pressurized air, laser, acoustics, etc. By using acoustics as an excitation technique it is easy to select an excitation signal going from random noise to a simple sine. Also the equipment to produce the acoustic excitation is rather cheap. However, the state of the art does not offer a straightforward technique to estimate the excitation force, making it difficult for applications such as experimental modal analysis. In this research, acoustic excitation is compared with hammer excitation to estimate the frequency response function of two shafts. Especially a method to validate the force induced by the acoustics is derived. The final purpose of this research is to estimate the damping properties of rotating machinery

FAIRSECO: An Extensible Framework for Impact Measurement of Research Software

The growing usage of research software in the research community has highlighted the need to recognize and acknowledge the contributions made not only by researchers but also by Research Software Engineers. However, the existing methods for crediting research software and Research Software Engineers have proven to be insufficient. In response, we have developed FAIRSECO, an extensible open source framework with the objective of assessing the impact of research software in research through the evaluation of various factors. The FAIRSECO framework addresses two critical information needs: firstly, it provides potential users of research software with metrics related to software quality and FAIRness. Secondly, the framework provides information for those who wish to measure the success of a project by offering impact data. By exploring the quality and impact of research software, our aim is to ensure that Research Software Engineers receive the recognition they deserve for their valuable contributions.</p

A Decentralized Service Control Framework for Decentralized Applications in Cloud Environments

Effectively managing decentralized applications in cloud environments using a decentralized control paradigm is essential, as current cloud providers usually only offer a control interface for monitoring cloud infrastructures. This study proposes a decentralized service control framework for implementing the control across various organizations and coordinating collaboration among operators in a decentralized application. The proposed framework allows a consortium of organizations to control a shared distributed cloud infrastructure decentralized reliably. A consensus mechanism within the framework enables mutual coordination between the operators. This mechanism also uses an incentive protocol to enforce pro-active behavior and collaboration. We implement the framework with Hyperledger Fabric, and our experiments demonstrate its usability, reliability, and acceptable performance

A Decentralized Service Control Framework for Decentralized Applications in Cloud Environments

Effectively managing decentralized applications in cloud environments using a decentralized control paradigm is essential, as current cloud providers usually only offer a control interface for monitoring cloud infrastructures. This study proposes a decentralized service control framework for implementing the control across various organizations and coordinating collaboration among operators in a decentralized application. The proposed framework allows a consortium of organizations to control a shared distributed cloud infrastructure decentralized reliably. A consensus mechanism within the framework enables mutual coordination between the operators. This mechanism also uses an incentive protocol to enforce pro-active behavior and collaboration. We implement the framework with Hyperledger Fabric, and our experiments demonstrate its usability, reliability, and acceptable performance