A Dialog With Socrates Digital™

In this chapter, the presented example dialog shows how Socrates DigitalTM can guide users to learn and solve big and disparate data problems. In this example dialog, Socrates DigitalTM takes the lead—as a human instructor or facilitator would—to guide the conversation with the user groups. It begins by guiding user groups in the examination of information, concepts, and assumptions. Next, Socrates DigitalTM guides user groups to form conclusions and their implications. Finally, it guides user groups to summarize the conversation into a viewpoint about answering the question at hand.

Unsettled Aspects of the Digital Thread in Additive Manufacturing

In the past years, additive manufacturing (AM), also known as “3D printing,” has transitioned from rapid prototyping to making parts with potentially long service lives. Now AM provides the ability to have an almost fully digital chain from part design through manufacture and service. Web searches will reveal many statements that AM can help an organization in its pursuit of a “digital thread.” Equally, it is often stated that a digital thread may bring great benefits in improving designs, processes, materials, operations, and the ability to predict failure in a way that maximizes safety and minimizes cost and downtime. Now that the capability is emerging, a whole series of new questions begin to surface as well: •• What data should be stored, how will it be stored, and how much space will it require? •• What is the cost-to-benefit ratio of having a digital thread? •• Who owns the data and who can access and analyze it? •• How long will the data be stored and who will store it? •• How will the data remain readable and usable over the lifetime of a product? •• How much manipulation of disparate data is necessary for analysis without losing information? •• How will the data be secured, and its provenance validated? •• How does an enterprise accomplish configuration management of, and linkages between, data that may be distributed across multiple organizations? •• How do we determine what is “authoritative” in such an environment? These, along with many other questions, mark the combination of AM with a digital thread as an unsettled issue. As the seventh title in a series of SAE EDGE™ Research Reports on AM, this report discusses what the interplay between AM and a digital thread in the mobility industry would look like. This outlook includes the potential benefits and costs, the hurdles that need to be overcome for the combination to be useful, and how an organization can answer these questions to scope and benefit from the combination. This report, like the others in the series, is directed at a product team that is implementing AM. Unlike most of the other reports, putting the infrastructure in place, addressing the issues, and taking full advantage of the benefits will often fall outside of the purview of the product team and at the higher organizational, customer, and industry levels.

Developmental Acquisition of p53 Functions

Remarkably, the p53 transcription factor, referred to as “the guardian of the genome”, is not essential for mammalian development. Moreover, efforts to identify p53dependent developmental events have produced contradictory conclusions. Given the importance of pluripotent stem cells as models of mammalian development, and their applications in regenerative medicine and disease, resolving these conflicts is essential. Here we attempt to reconcile disparate data into justifiable conclusions predicated on reports that p53dependent transcription is first detected in late mouse blastocysts, that p53 activity first becomes potentially lethal during gastrulation, and that apoptosis does not depend on p53. Furthermore, p53 does not regulate expression of genes required for pluripotency in embryonic stem cells (ESCs); it contributes to ESC genomic stability and differentiation. Depending on conditions, p53 accelerates initiation of apoptosis in ESCs in response to DNA damage, but cell cycle arrest as well as the rate and extent of apoptosis in ESCs are p53-independent. In embryonic fibroblasts, p53 induces cell cycle arrest to allow repair of DNA damage, and cell senescence to prevent proliferation of cells with extensive damage.

BioThings SDK: a toolkit for building high-performance data APIs in biomedical research

To meet the increased need of making biomedical resources more accessible and reusable, Web APIs or web services have become a common way to disseminate knowledge sources. The BioThings APIs are a collection of high-performance, scalable, annotation as a service APIs that automate the integration of biological annotations from disparate data sources. This collection of APIs currently includes MyGene.info, MyVariant.info, and MyChem.info for integrating annotations on genes, variants, and chemical compounds, respectively. These APIs are used by both individual researchers and application developers to simplify the process of annotation retrieval and identifier mapping. Here, we describe the BioThings Software Development Kit (SDK), a generalizable and reusable toolkit for integrating data from multiple disparate data sources and creating high-performance APIs. This toolkit allows users to easily create their own BioThings APIs for any data type of interest to them, as well as keep APIs up-to-date with their underlying data sources. Availability and implementation: The BioThings SDK is built in Python and released via PyPI (https://pypi.org/project/biothings/). Its source code is hosted at its github repository (https://github.com/biothings/biothings.api).

Developmental Acquisition of p53 Functions

Remarkably, the p53 transcription factor, referred to as “the guardian of the genome”, is not essential for mammalian development. Moreover, efforts to identify p53‑dependent developmental events have produced contradictory conclusions. Given the importance of pluripotent stem cells as models of mammalian development, and their applications in regenerative medicine and disease, resolving these conflicts is essential. Here we attempt to reconcile disparate data into justifiable conclusions predicated on reports that p53‑dependent transcription is first detected in late mouse blastocysts, that p53 activity first becomes potentially lethal during gastrulation, and that apoptosis does not depend on p53. Furthermore, p53 does not regulate expression of genes required for pluripotency in embryonic stem cells (ESCs); it contributes to ESC genomic stability and differentiation. Depending on conditions, p53 accelerates initiation of apoptosis in ESCs in response to DNA damage, but cell cycle arrest as well as the rate and extent of apoptosis in ESCs are p53-independent. In embryonic fibroblasts, p53 induces cell cycle arrest to allow repair of DNA damage, and cell senescence to prevent proliferation of cells with extensive damage.

easyFulcrum: An R package to process and analyze ecological sampling data generated using the Fulcrum mobile application

Large-scale ecological sampling can be difficult and costly, especially for organisms that are too small to be easily identified in a natural environment by eye. Typically, these microscopic floral and fauna are sampled by collecting substrates from nature and then separating organisms from substrates in the laboratory. In many cases, diverse organisms can be identified to the species-level using molecular barcodes. To facilitate large-scale ecological sampling of microscopic organisms, we used a geographic data-collection platform for mobile devices called Fulcrum that streamlines the organization of geospatial sampling data, substrate photographs, and environmental data at natural sampling sites. These sampling data are then linked to organism isolation data from the laboratory. Here, we describe the easyFulcrum R package, which can be used to clean, process, and visualize ecological field sampling and isolation data exported from the Fulcrum mobile application. We developed this package for wild nematode sampling, but it can be used with other organisms. The advantages of using Fulcrum combined with easyFulcrum are (1) the elimination of transcription errors by replacing manual data entry and/or spreadsheets with a mobile application, (2) the ability to clean, process, and visualize sampling data using a standardized set of functions in the R software environment, and (3) the ability to join disparate data to each other, including environmental data from the field and the molecularly defined identities of individual specimens isolated from samples.

Identifying At-Risk Communities and Key Vulnerability Indicators in the COVID-19 Pandemic

Throughout the COVID-19 pandemic, certain communities have been disproportionately exposed to detrimental health outcomes and socioeconomic injuries. Quantifying community needs is crucial for identifying testing and service deserts, effectively allocating resources, and informing funding and decision making. We have constructed research-driven metrics measuring the public health and economic impacts of COVID-19 on vulnerable populations. In this work we further examine and validate these indices by training supervised models to predict proxy outcomes and analyzing the feature importances to identify gaps in our original metric design. The indices analyzed in this work are unique among COVID-19 risk assessments due to their robust integration of disparate data sources. Together, they enable more effective responses to COVID-19 driven health inequities.

easyFulcrum: An R package to process and analyze ecological sampling data generated using the Fulcrum mobile application

Large-scale ecological sampling can be difficult and costly, especially for organisms that are too small to be easily identified in a natural environment by eye. Typically, these microscopic floral and fauna are sampled by collecting substrates from nature and then separating organisms from substrates in the laboratory. In many cases, diverse organisms can be identified to the species-level using molecular barcodes. To facilitate large-scale ecological sampling of microscopic organisms, we used a geographic data-collection platform for mobile devices called Fulcrum that streamlines the organization of geospatial sampling data, substrate photographs, and environmental data at natural sampling sites. These sampling data are then linked to organism isolation data from the laboratory. Here, we describe the easyFulcrum R package, which can be used to clean, process, and visualize ecological field sampling and isolation data exported from the Fulcrum mobile application. We developed this package for wild nematode sampling, but it is extensible to other organisms. The advantages of using Fulcrum combined with easyFulcrum are (1) the elimination of transcription errors by replacing manual data entry and/or spreadsheets with a mobile application, (2) the ability to clean, process, and visualize sampling data using a standardized set of functions in the R software environment, and (3) the ability to join disparate data to each other, including environmental data from the field and the molecularly defined identities of individual specimens isolated from samples.

Model-based Approach to Multi-domain Monitoring Data Aggregation

The essential propellant for any closed-loop management mechanism is data related to the managed entity. While this is a general evidence, it becomes even more true when dealing with advanced closed-loop systems like the ones supported by Artificial Intelligence (AI), as they require a trustworthy, up-to-date and steady flow of state data to be applicable. Modern network infrastructures provide a vast amount of disparate data sources, especially in the multi-domain scenarios considered by the ETSI Industry Specification Group (ISG) Zero Touch Network and Service Management (ZSM) framework, and proper mechanisms for data aggregation, pre-processing and normalization are required to make possible AI-enabled closed-loop management. So far, solutions proposed for these data aggregation tasks have been specific to concrete data sources and consumers, following ad-hoc approaches unsuitable to address the vast heterogeneity of data sources and potential data consumers. This paper presents a model-based approach to a data aggregator framework, relying on standardized data models and telemetry protocols, and integrated with an open-source network orchestration stack to support their incorporation within network service lifecycles.